Bruce A. Thyer
- Published in print:
- 2012
- Published Online:
- May 2012
- ISBN:
- 9780195387384
- eISBN:
- 9780199932085
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195387384.001.0001
- Subject:
- Social Work, Research and Evaluation
Quasi-experimental research designs are the most widely used research approach employed to evaluate the outcomes of social work programs and policies. This new volume describes the logic, design, and ...
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Quasi-experimental research designs are the most widely used research approach employed to evaluate the outcomes of social work programs and policies. This new volume describes the logic, design, and conduct of the range of such designs, encompassing pre-experiments, quasi-experiments making use of a control or comparison group, and time-series designs. An introductory chapter describes the valuable role these types of studies have played in social work, going back to the 1930s, and continuing to the present. Subsequent chapters describe the major features of individual quasi-experimental designs, the types of questions they are capable of answering, and their strengths and limitations. Each discussion of these designs presented in the abstract is subsequently illustrated with descriptions of real examples of their use as published in the social work literature and related fields. By linking the discussion of quasi-experimental designs in the abstract to actual applications to evaluate the outcomes of social services, the usefulness and vitality of these research methods comes alive to the reader. While this volume could be used as a research textbook, it will also have great value to practitioners seeking a greater conceptual understanding of the quasi-experimental studies they frequently read about in the social work literature. Human service professionals planning to undertake a program evaluation of their own agency's services will find this book of immense help in understanding the steps and actions needed to adopt a quasi-experimental strategy. It is usually the case that ethical and pragmatic considerations preclude the use of randomly assigning social work clients to experimental and comparative treatment conditions, and in such instances, the practicality of employing a quasi-experimental method becomes an excellent alternative.Less
Quasi-experimental research designs are the most widely used research approach employed to evaluate the outcomes of social work programs and policies. This new volume describes the logic, design, and conduct of the range of such designs, encompassing pre-experiments, quasi-experiments making use of a control or comparison group, and time-series designs. An introductory chapter describes the valuable role these types of studies have played in social work, going back to the 1930s, and continuing to the present. Subsequent chapters describe the major features of individual quasi-experimental designs, the types of questions they are capable of answering, and their strengths and limitations. Each discussion of these designs presented in the abstract is subsequently illustrated with descriptions of real examples of their use as published in the social work literature and related fields. By linking the discussion of quasi-experimental designs in the abstract to actual applications to evaluate the outcomes of social services, the usefulness and vitality of these research methods comes alive to the reader. While this volume could be used as a research textbook, it will also have great value to practitioners seeking a greater conceptual understanding of the quasi-experimental studies they frequently read about in the social work literature. Human service professionals planning to undertake a program evaluation of their own agency's services will find this book of immense help in understanding the steps and actions needed to adopt a quasi-experimental strategy. It is usually the case that ethical and pragmatic considerations preclude the use of randomly assigning social work clients to experimental and comparative treatment conditions, and in such instances, the practicality of employing a quasi-experimental method becomes an excellent alternative.
Stephanie A. Siler and David Klahr
- Published in print:
- 2012
- Published Online:
- September 2012
- ISBN:
- 9780199753628
- eISBN:
- 9780199950027
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199753628.003.0007
- Subject:
- Psychology, Cognitive Psychology, Social Psychology
Students come to science classes with preconceptions about the natural world and ways to explore that world to learn more about it. Students' prior beliefs may distort their understanding of how to ...
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Students come to science classes with preconceptions about the natural world and ways to explore that world to learn more about it. Students' prior beliefs may distort their understanding of how to design an experiment and also its purpose: to identify causal factors. These prior beliefs influence students' reasoning about experimentation, leading them to misconstrue instruction aimed at teaching them about the core component of experimental design: the Control of Variables Strategy (CVS). Many students erroneously interpret the instructional goal as to teach them some domain-specific knowledge or to produce a desired effect, rather than as how to execute a domain-general procedure for designing experiments. The behavior of late-elementary and middle school students is examined to categorize common misconceptions about the goal of the CVS instruction, describe how those misconceptions led to delays or failures in learning CVS, and suggest instructional procedures that can be used to remediate the misconceptions.Less
Students come to science classes with preconceptions about the natural world and ways to explore that world to learn more about it. Students' prior beliefs may distort their understanding of how to design an experiment and also its purpose: to identify causal factors. These prior beliefs influence students' reasoning about experimentation, leading them to misconstrue instruction aimed at teaching them about the core component of experimental design: the Control of Variables Strategy (CVS). Many students erroneously interpret the instructional goal as to teach them some domain-specific knowledge or to produce a desired effect, rather than as how to execute a domain-general procedure for designing experiments. The behavior of late-elementary and middle school students is examined to categorize common misconceptions about the goal of the CVS instruction, describe how those misconceptions led to delays or failures in learning CVS, and suggest instructional procedures that can be used to remediate the misconceptions.
David B. Resnik
- Published in print:
- 2007
- Published Online:
- January 2007
- ISBN:
- 9780195309782
- eISBN:
- 9780199871285
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195309782.003.0004
- Subject:
- Philosophy, Moral Philosophy
This chapter considers the various ways that money can interfere with scientific norms. Problems can occur when financial interests intrude into experimental design, data analysis and interpretation, ...
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This chapter considers the various ways that money can interfere with scientific norms. Problems can occur when financial interests intrude into experimental design, data analysis and interpretation, publication, peer review, and other aspects of science that should be protected from financial, political, or other biases. When this happens, financial interests affect the process of scientific research, and they can undermine objectivity, openness, honesty, and other research norms. Although it is impossible to prevent money from having any impact on research, society should take some steps to prevent financial interests from undermining scientific norms, such as developing policies for journals, granting agencies, and research institutions; educating students and scientists about potential problems and issues; and monitoring of research.Less
This chapter considers the various ways that money can interfere with scientific norms. Problems can occur when financial interests intrude into experimental design, data analysis and interpretation, publication, peer review, and other aspects of science that should be protected from financial, political, or other biases. When this happens, financial interests affect the process of scientific research, and they can undermine objectivity, openness, honesty, and other research norms. Although it is impossible to prevent money from having any impact on research, society should take some steps to prevent financial interests from undermining scientific norms, such as developing policies for journals, granting agencies, and research institutions; educating students and scientists about potential problems and issues; and monitoring of research.
Peter Lyons and Howard J. Doueck
- Published in print:
- 2009
- Published Online:
- February 2010
- ISBN:
- 9780195373912
- eISBN:
- 9780199865604
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195373912.003.0004
- Subject:
- Social Work, Research and Evaluation
This chapter describes ethical issues in social research including discussion of the NASW Code of Ethics, Institutional Review Board (IRB) processes, and requirements for the protection of human ...
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This chapter describes ethical issues in social research including discussion of the NASW Code of Ethics, Institutional Review Board (IRB) processes, and requirements for the protection of human subjects. In addition, quantitative research methods; qualitative research methods; mixed-methods research designs; experimental, quasi-experimental, explanatory, exploratory, and descriptive research; program evaluation; and the relative merits of disparate models of research are also presented. The requirements of rigor in both quantitative and qualitative studies and evaluating the degree of fit between research strategies and problems under investigation are also discussed.Less
This chapter describes ethical issues in social research including discussion of the NASW Code of Ethics, Institutional Review Board (IRB) processes, and requirements for the protection of human subjects. In addition, quantitative research methods; qualitative research methods; mixed-methods research designs; experimental, quasi-experimental, explanatory, exploratory, and descriptive research; program evaluation; and the relative merits of disparate models of research are also presented. The requirements of rigor in both quantitative and qualitative studies and evaluating the degree of fit between research strategies and problems under investigation are also discussed.
Phyllis Solomon, Mary M. Cavanaugh, and Jeffrey Draine
- Published in print:
- 2009
- Published Online:
- May 2009
- ISBN:
- 9780195333190
- eISBN:
- 9780199864317
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195333190.003.0001
- Subject:
- Social Work, Research and Evaluation
Randomized controlled trials (RCTs) are considered the gold standard of scientific evidence when determining the effectiveness of policy and practice interventions. In order to understand the basis ...
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Randomized controlled trials (RCTs) are considered the gold standard of scientific evidence when determining the effectiveness of policy and practice interventions. In order to understand the basis for the importance and utility of RCTs to community-based psychosocial interventions, Chapter 1 outlines the following: 1) establishes a definition of RCTs within the context of real-world service delivery systems, 2) distinguishes RCTs from program evaluations and from quasi-experimental and pre-experimental designs, 3) discusses the significance of RCTs to evidence-based practice, and 4) provides an overview of the following chapters, which offer practical guidance in designing, planning, and conducting RCTs for social work practice, using case examples to illustrate the material presented. In addition, Chapter 1 defines the term “community-based psychosocial interventions” as reflecting the grounding of interventions in impacting the social context of the individual, as well as the inherent change within the individual.Less
Randomized controlled trials (RCTs) are considered the gold standard of scientific evidence when determining the effectiveness of policy and practice interventions. In order to understand the basis for the importance and utility of RCTs to community-based psychosocial interventions, Chapter 1 outlines the following: 1) establishes a definition of RCTs within the context of real-world service delivery systems, 2) distinguishes RCTs from program evaluations and from quasi-experimental and pre-experimental designs, 3) discusses the significance of RCTs to evidence-based practice, and 4) provides an overview of the following chapters, which offer practical guidance in designing, planning, and conducting RCTs for social work practice, using case examples to illustrate the material presented. In addition, Chapter 1 defines the term “community-based psychosocial interventions” as reflecting the grounding of interventions in impacting the social context of the individual, as well as the inherent change within the individual.
Fabrizio Benedetti
- Published in print:
- 2008
- Published Online:
- September 2009
- ISBN:
- 9780199559121
- eISBN:
- 9780191724022
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199559121.003.0011
- Subject:
- Neuroscience, Molecular and Cellular Systems
To study a placebo effect requires specific designs that cannot be performed in the classic clinical trial setting. Complex experimental designs are particularly necessary when one wants to ...
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To study a placebo effect requires specific designs that cannot be performed in the classic clinical trial setting. Complex experimental designs are particularly necessary when one wants to investigate the neurobiological mechanisms, for example by means of agonist and antagonist drugs. Complex pharmacological designs have used up to twelve experimental arms (groups) in order to answer specific questions. To study the role of learning in placebo effects, for example conditioning, one needs to control the associations between conditioned and unconditioned stimuli both in the experimental and in the clinical setting. As to the open-hidden paradigm, several approaches are possible to hide a therapy from the subject's view, so that he is totally unaware that a treatment is being performed.Less
To study a placebo effect requires specific designs that cannot be performed in the classic clinical trial setting. Complex experimental designs are particularly necessary when one wants to investigate the neurobiological mechanisms, for example by means of agonist and antagonist drugs. Complex pharmacological designs have used up to twelve experimental arms (groups) in order to answer specific questions. To study the role of learning in placebo effects, for example conditioning, one needs to control the associations between conditioned and unconditioned stimuli both in the experimental and in the clinical setting. As to the open-hidden paradigm, several approaches are possible to hide a therapy from the subject's view, so that he is totally unaware that a treatment is being performed.
Corey J. A. Bradshaw and Barry W. Brook
- Published in print:
- 2010
- Published Online:
- February 2010
- ISBN:
- 9780199554232
- eISBN:
- 9780191720666
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199554232.003.0017
- Subject:
- Biology, Ecology, Biodiversity / Conservation Biology
In this chapter, Corey J. A. Bradshaw and Barry W. Brook, discuss measures of biodiversity patterns followed by an overview of experimental design and associated statistical paradigms. Conservation ...
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In this chapter, Corey J. A. Bradshaw and Barry W. Brook, discuss measures of biodiversity patterns followed by an overview of experimental design and associated statistical paradigms. Conservation biology is a highly multidisciplinary science employing methods from ecology, Earth systems science, genetics, physiology, veterinary science, medicine, mathematics, climatology, anthropology, psychology, sociology, environmental policy, geography, political science, and resource management. Here we focus primarily on ecological methods and experimental design. It is impossible to census all species in an ecosystem, so many different measures exist to compare biodiversity: these include indices such as species richness, Simpson's diversity, Shannon's index and Brouillin's index. Many variants of these indices exist. The scale of biodiversity patterns is important to consider for biodiversity comparisons: α (local), β (between‐site), and γ (regional or continental) diversity. Often surrogate species ‐ the number, distribution or pattern of species in a particular taxon in a particular area thought to indicate a much wider array of taxa ‐ are required to simplify biodiversity assessments. Many similarity, dissimilarity, clustering, and multivariate techniques are available to compare biodiversity indices among sites. Conservation biology rarely uses completely manipulative experimental designs (although there are exceptions), with mensurative (based on existing environmental gradients) and observational studies dominating. Two main statistical paradigms exist for comparing biodiversity: null hypothesis testing and multiple working hypotheses – the latter paradigm is more consistent with the constraints typical of conservation data and so should be invoked when possible. Bayesian inferential methods generally provide more certainty when prior data exist. Large sample sizes, appropriate replication and randomization are cornerstone concepts in all conservation experiments. Simple relative abundance time series (sequential counts of individuals) can be used to infer more complex ecological mechanisms that permit the estimation of extinction risk, population trends, and intrinsic feedbacks. The risk of a species going extinct or becoming invasive can be predicted using cross‐taxonomic comparisons of life history traits. Population viability analyses are essential tools to estimate extinction risk over defined periods and under particular management interventions. Many methods exist to implement these, including count‐based, demographic, metapopulation, and genetic. Many tools exist to examine how genetics affects extinction risk, of which perhaps the measurement of inbreeding depression, gene flow among populations, and the loss of genetic diversity with habitat degradation are the most important.Less
In this chapter, Corey J. A. Bradshaw and Barry W. Brook, discuss measures of biodiversity patterns followed by an overview of experimental design and associated statistical paradigms. Conservation biology is a highly multidisciplinary science employing methods from ecology, Earth systems science, genetics, physiology, veterinary science, medicine, mathematics, climatology, anthropology, psychology, sociology, environmental policy, geography, political science, and resource management. Here we focus primarily on ecological methods and experimental design. It is impossible to census all species in an ecosystem, so many different measures exist to compare biodiversity: these include indices such as species richness, Simpson's diversity, Shannon's index and Brouillin's index. Many variants of these indices exist. The scale of biodiversity patterns is important to consider for biodiversity comparisons: α (local), β (between‐site), and γ (regional or continental) diversity. Often surrogate species ‐ the number, distribution or pattern of species in a particular taxon in a particular area thought to indicate a much wider array of taxa ‐ are required to simplify biodiversity assessments. Many similarity, dissimilarity, clustering, and multivariate techniques are available to compare biodiversity indices among sites. Conservation biology rarely uses completely manipulative experimental designs (although there are exceptions), with mensurative (based on existing environmental gradients) and observational studies dominating. Two main statistical paradigms exist for comparing biodiversity: null hypothesis testing and multiple working hypotheses – the latter paradigm is more consistent with the constraints typical of conservation data and so should be invoked when possible. Bayesian inferential methods generally provide more certainty when prior data exist. Large sample sizes, appropriate replication and randomization are cornerstone concepts in all conservation experiments. Simple relative abundance time series (sequential counts of individuals) can be used to infer more complex ecological mechanisms that permit the estimation of extinction risk, population trends, and intrinsic feedbacks. The risk of a species going extinct or becoming invasive can be predicted using cross‐taxonomic comparisons of life history traits. Population viability analyses are essential tools to estimate extinction risk over defined periods and under particular management interventions. Many methods exist to implement these, including count‐based, demographic, metapopulation, and genetic. Many tools exist to examine how genetics affects extinction risk, of which perhaps the measurement of inbreeding depression, gene flow among populations, and the loss of genetic diversity with habitat degradation are the most important.
Bruce A Thyer
- Published in print:
- 2012
- Published Online:
- May 2012
- ISBN:
- 9780195387384
- eISBN:
- 9780199932085
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195387384.003.0002
- Subject:
- Social Work, Research and Evaluation
The simplest of the group research designs involve the assessment of the functioning of a single group of persons who receive social work services. These methods are called pre-experimental designs. ...
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The simplest of the group research designs involve the assessment of the functioning of a single group of persons who receive social work services. These methods are called pre-experimental designs. Tightly controlled studies done in laboratory or special treatment settings are known as efficacy studies, and are used to demonstrate if a given treatment can produce positive results under ideal conditions. Outcome studies done with more clinically representative clients and therapists, in real world agency settings, are known as effectiveness studies. Ideally the latter are conducted after the former, under conditions of increasing complexity, so as to determine treatments that work well in real-world contexts. Among the pre-experimental designs are the one group posttreatment-only study and the one group pretest-posttest design. Various ways in which these designs can be strengthened are presented, along with descriptions of published articles illustrating their use in social work and other human service settings. The limitations of these designs are also discussed, as is a review of the major threats to internal validity that can inhibit causal inferences.Less
The simplest of the group research designs involve the assessment of the functioning of a single group of persons who receive social work services. These methods are called pre-experimental designs. Tightly controlled studies done in laboratory or special treatment settings are known as efficacy studies, and are used to demonstrate if a given treatment can produce positive results under ideal conditions. Outcome studies done with more clinically representative clients and therapists, in real world agency settings, are known as effectiveness studies. Ideally the latter are conducted after the former, under conditions of increasing complexity, so as to determine treatments that work well in real-world contexts. Among the pre-experimental designs are the one group posttreatment-only study and the one group pretest-posttest design. Various ways in which these designs can be strengthened are presented, along with descriptions of published articles illustrating their use in social work and other human service settings. The limitations of these designs are also discussed, as is a review of the major threats to internal validity that can inhibit causal inferences.
Wiktor L. Adamowicz, Peter C. Boxall, Jordan J. Louviere, Joffre Swait, and Michael Williams
- Published in print:
- 2001
- Published Online:
- November 2003
- ISBN:
- 9780199248919
- eISBN:
- 9780191595950
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199248915.003.0013
- Subject:
- Economics and Finance, Development, Growth, and Environmental
The stated preference (SP) approach allows the individual features or attributes that make up a good to be valued. Experimental design to array attributes and attribute levels into choice sets is ...
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The stated preference (SP) approach allows the individual features or attributes that make up a good to be valued. Experimental design to array attributes and attribute levels into choice sets is fundamental to SP. Respondents typically select one of two choice sets, along with the status quo alternative. SP has a number of advantages over other environmental valuation methods, such as orthogonality in attributes, which avoids colinearity problems of revealed preference methods. An application of SP to mouse hunting in Canada is presented.Less
The stated preference (SP) approach allows the individual features or attributes that make up a good to be valued. Experimental design to array attributes and attribute levels into choice sets is fundamental to SP. Respondents typically select one of two choice sets, along with the status quo alternative. SP has a number of advantages over other environmental valuation methods, such as orthogonality in attributes, which avoids colinearity problems of revealed preference methods. An application of SP to mouse hunting in Canada is presented.
R. Duncan Luce
- Published in print:
- 1991
- Published Online:
- January 2008
- ISBN:
- 9780195070019
- eISBN:
- 9780199869879
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195070019.003.0010
- Subject:
- Psychology, Cognitive Models and Architectures
This chapter discusses major reaction-time results for experimental designs with more than two signals. Topics covered include impact of number of signals; sequential effects; and experiments with ...
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This chapter discusses major reaction-time results for experimental designs with more than two signals. Topics covered include impact of number of signals; sequential effects; and experiments with errors.Less
This chapter discusses major reaction-time results for experimental designs with more than two signals. Topics covered include impact of number of signals; sequential effects; and experiments with errors.
Bruce A Thyer
- Published in print:
- 2012
- Published Online:
- May 2012
- ISBN:
- 9780195387384
- eISBN:
- 9780199932085
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195387384.003.0003
- Subject:
- Social Work, Research and Evaluation
The quasi-experimental designs compare the outcomes of social work for a group of clients who receive a novel intervention that is the focus on investigation, against the outcomes observed by a ...
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The quasi-experimental designs compare the outcomes of social work for a group of clients who receive a novel intervention that is the focus on investigation, against the outcomes observed by a similar group of clients who received either no treatment (a control group) or an alternative treatment (a comparison group). Among these methods are the posttest-only control group design, the posttest-only comparison group design, the pretest-posttest no-treatment control group design, the pretest-posttest alternative treatment comparison group design, the swtiching replications design, and dismantling studies, wherein a 'complete' intervention's outcomes are compared with the outcomes following receipt of a partial intervention. The role of placebo control groups is introduced as a means of providing a more rigorous appraisal of the specific effects of an intervention, compared to its nonspecific effects.Less
The quasi-experimental designs compare the outcomes of social work for a group of clients who receive a novel intervention that is the focus on investigation, against the outcomes observed by a similar group of clients who received either no treatment (a control group) or an alternative treatment (a comparison group). Among these methods are the posttest-only control group design, the posttest-only comparison group design, the pretest-posttest no-treatment control group design, the pretest-posttest alternative treatment comparison group design, the swtiching replications design, and dismantling studies, wherein a 'complete' intervention's outcomes are compared with the outcomes following receipt of a partial intervention. The role of placebo control groups is introduced as a means of providing a more rigorous appraisal of the specific effects of an intervention, compared to its nonspecific effects.
Ignacio Palacios-Huerta
- Published in print:
- 2014
- Published Online:
- October 2017
- ISBN:
- 9780691144023
- eISBN:
- 9781400850310
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691144023.003.0004
- Subject:
- Economics and Finance, History of Economic Thought
Chapter 2 showed that when the exact question being asked is mirrored in a laboratory experiment and the population being studied is the same as in the field, the outcomes from the experiment can be ...
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Chapter 2 showed that when the exact question being asked is mirrored in a laboratory experiment and the population being studied is the same as in the field, the outcomes from the experiment can be just as clear and informative. This result suggests that when either the exact question being asked is not mirrored or the population being studied differs, the outcomes from the experiment probably do not parallel those observed in the field. This chapter uses this insight to draw four lessons for experimental design using the games, methods, and results from the previous chapters. Among these lessons are that Major League Soccer players would not be an appropriate pool of subjects to conduct the type of study implemented in Chapter 2, and that a zero-sum situation played among friends does not represent the way subjects interact in the field.Less
Chapter 2 showed that when the exact question being asked is mirrored in a laboratory experiment and the population being studied is the same as in the field, the outcomes from the experiment can be just as clear and informative. This result suggests that when either the exact question being asked is not mirrored or the population being studied differs, the outcomes from the experiment probably do not parallel those observed in the field. This chapter uses this insight to draw four lessons for experimental design using the games, methods, and results from the previous chapters. Among these lessons are that Major League Soccer players would not be an appropriate pool of subjects to conduct the type of study implemented in Chapter 2, and that a zero-sum situation played among friends does not represent the way subjects interact in the field.
Annie Britton
- Published in print:
- 2010
- Published Online:
- September 2010
- ISBN:
- 9780199569298
- eISBN:
- 9780191594427
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199569298.003.0004
- Subject:
- Public Health and Epidemiology, Public Health
An experimental study is the standard method for evaluating the effectiveness of a health or medical intervention. In such a study, a group of people will be exposed to an intervention and then ...
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An experimental study is the standard method for evaluating the effectiveness of a health or medical intervention. In such a study, a group of people will be exposed to an intervention and then compared with another group (a control group) who have not been exposed, or with a group who had a different intervention. There are situations in which an experimental approach may not be feasible, ethical, or practical, but, when possible, well-designed controlled experiments provide reliable evidence on the effectiveness of interventions and inform the policies and practice of health promotion. This chapter discusses different experimental designs, explores their strengths and weaknesses, and determines how the most appropriate design might be chosen in light of the many unique features of health promotion interventions. It shows that well-conducted randomized controlled trials (RCTs) are a valid and important way of evaluating health promotion interventions.Less
An experimental study is the standard method for evaluating the effectiveness of a health or medical intervention. In such a study, a group of people will be exposed to an intervention and then compared with another group (a control group) who have not been exposed, or with a group who had a different intervention. There are situations in which an experimental approach may not be feasible, ethical, or practical, but, when possible, well-designed controlled experiments provide reliable evidence on the effectiveness of interventions and inform the policies and practice of health promotion. This chapter discusses different experimental designs, explores their strengths and weaknesses, and determines how the most appropriate design might be chosen in light of the many unique features of health promotion interventions. It shows that well-conducted randomized controlled trials (RCTs) are a valid and important way of evaluating health promotion interventions.
Paul M. Beardsley, Mark V. Bloom, and Sarah B. Wise
- Published in print:
- 2012
- Published Online:
- September 2012
- ISBN:
- 9780199730421
- eISBN:
- 9780199949557
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199730421.003.0013
- Subject:
- Psychology, Developmental Psychology, Cognitive Psychology
This chapter summarizes studies (up to 2009) on approaches to teaching evolution that provide evidence of effectiveness for teaching about evolution. Few studies exist at the elementary and middle ...
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This chapter summarizes studies (up to 2009) on approaches to teaching evolution that provide evidence of effectiveness for teaching about evolution. Few studies exist at the elementary and middle school levels. At high school and undergraduate levels, a wide variety of results were reported. The lack of standard assessments and the variation in quality of assessments used limits comparisons among studies. Additionally, evolution education would benefit from more studies with rigorous experimental designs. With these limitations in mind, the review showed no support for lecture-based approaches, whereas inquiry-based and conceptual change approaches showed some evidence for support, especially when an appropriate amount of time was allotted. More research on the effect of making evolution relevant remains to be completed.Less
This chapter summarizes studies (up to 2009) on approaches to teaching evolution that provide evidence of effectiveness for teaching about evolution. Few studies exist at the elementary and middle school levels. At high school and undergraduate levels, a wide variety of results were reported. The lack of standard assessments and the variation in quality of assessments used limits comparisons among studies. Additionally, evolution education would benefit from more studies with rigorous experimental designs. With these limitations in mind, the review showed no support for lecture-based approaches, whereas inquiry-based and conceptual change approaches showed some evidence for support, especially when an appropriate amount of time was allotted. More research on the effect of making evolution relevant remains to be completed.
Jane Costello and Adrian Angold
- Published in print:
- 2007
- Published Online:
- September 2009
- ISBN:
- 9780198528487
- eISBN:
- 9780191723940
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198528487.003.0002
- Subject:
- Public Health and Epidemiology, Public Health, Epidemiology
This chapter reviews methods for studying individual differences across the life course. It starts from the position that even when a life course study is basically observational or descriptive, ...
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This chapter reviews methods for studying individual differences across the life course. It starts from the position that even when a life course study is basically observational or descriptive, there is an underlying concern to understand more about causality. There are two aspects of research methods that have to be considered in designing a life course study: study design and measurement of individuals. Under the first heading the chapter describes observational and quasi-experimental designs for life course research. A section on genetically informative designs describes a range of options for increasing the genetic information that can be obtained from life course research. The section on capturing individual differences discusses continuous versus categorical measurement, the timing of measurements, the range of information that can be collected, and non-intrusive methods for collecting individual life course information. A section on biological information discusses applications of molecular genetics and psychoneuroendocrinology to life course research.Less
This chapter reviews methods for studying individual differences across the life course. It starts from the position that even when a life course study is basically observational or descriptive, there is an underlying concern to understand more about causality. There are two aspects of research methods that have to be considered in designing a life course study: study design and measurement of individuals. Under the first heading the chapter describes observational and quasi-experimental designs for life course research. A section on genetically informative designs describes a range of options for increasing the genetic information that can be obtained from life course research. The section on capturing individual differences discusses continuous versus categorical measurement, the timing of measurements, the range of information that can be collected, and non-intrusive methods for collecting individual life course information. A section on biological information discusses applications of molecular genetics and psychoneuroendocrinology to life course research.
Anne E. Magurran
- Published in print:
- 2005
- Published Online:
- September 2007
- ISBN:
- 9780198527855
- eISBN:
- 9780191713576
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198527855.003.0008
- Subject:
- Biology, Evolutionary Biology / Genetics
This concluding chapter draws together the main themes of the book before summarizing the legacy of the pioneer guppy researchers. It identifies some areas where research is likely to be directed in ...
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This concluding chapter draws together the main themes of the book before summarizing the legacy of the pioneer guppy researchers. It identifies some areas where research is likely to be directed in future. These include the application of genomic tools and analyses of multi-trait evolution. There are three main conclusions. First, quality empirical work (such as behavioural observation and ecological recording) is of lasting value. The Trinidadian guppy system illustrates well how durable good data are. Second, investigations involving the guppy have led to significant advances in evolutionary ecology. It is a uniquely tractable vertebrate system. Lab studies can be dovetailed with field observations and manipulations. In addition, the guppy illustrates beautifully how changes in one trait, for example predator avoidance, impinge on others such as mating behaviour. Finally, the guppy system will continue to offer unrivalled opportunities to test theories in evolutionary ecology. The book concludes with a plea that the system be safeguarded.Less
This concluding chapter draws together the main themes of the book before summarizing the legacy of the pioneer guppy researchers. It identifies some areas where research is likely to be directed in future. These include the application of genomic tools and analyses of multi-trait evolution. There are three main conclusions. First, quality empirical work (such as behavioural observation and ecological recording) is of lasting value. The Trinidadian guppy system illustrates well how durable good data are. Second, investigations involving the guppy have led to significant advances in evolutionary ecology. It is a uniquely tractable vertebrate system. Lab studies can be dovetailed with field observations and manipulations. In addition, the guppy illustrates beautifully how changes in one trait, for example predator avoidance, impinge on others such as mating behaviour. Finally, the guppy system will continue to offer unrivalled opportunities to test theories in evolutionary ecology. The book concludes with a plea that the system be safeguarded.
Peter J. Diggle and Amanda G. Chetwynd
- Published in print:
- 2011
- Published Online:
- December 2013
- ISBN:
- 9780199543182
- eISBN:
- 9780191774867
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199543182.001.0001
- Subject:
- Mathematics, Probability / Statistics, Biostatistics
An antidote to technique-oriented service courses, this book studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to ...
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An antidote to technique-oriented service courses, this book studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, it aims to give the reader a clear understanding of how core statistical ideas of experimental design, modelling, and data analysis are integral to the scientific method. Aimed primarily towards a range of scientific disciplines (albeit with a bias towards the biological, environmental, and health sciences), this book assumes some maturity of understanding of scientific method, but does not require any prior knowledge of statistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation. Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice. All of the material in the book can be understood without using either R or any other computer software.Less
An antidote to technique-oriented service courses, this book studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, it aims to give the reader a clear understanding of how core statistical ideas of experimental design, modelling, and data analysis are integral to the scientific method. Aimed primarily towards a range of scientific disciplines (albeit with a bias towards the biological, environmental, and health sciences), this book assumes some maturity of understanding of scientific method, but does not require any prior knowledge of statistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation. Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice. All of the material in the book can be understood without using either R or any other computer software.
Bas C. van Fraassen
- Published in print:
- 1980
- Published Online:
- November 2003
- ISBN:
- 9780198244271
- eISBN:
- 9780191597473
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198244274.003.0004
- Subject:
- Philosophy, Philosophy of Science
Scientific theories do much more than answer empirical questions. This can be understood along empiricist lines only if those other aspects are instrumental for the pursuit of empirical strength and ...
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Scientific theories do much more than answer empirical questions. This can be understood along empiricist lines only if those other aspects are instrumental for the pursuit of empirical strength and adequacy, or serving other aims subordinate to these. This chapter accordingly addresses four main questions: (1) Does the rejection of realism lead to a self‐defeating scepticism? (2) Are scientific methodology and experimental design intelligible on any but a realist interpretation of science? (3) Is the ideal of the unity of science, or even the practice of using distinct theories in conjunction, intelligent on an empiricist view? (4) What sense can an empiricist position accord to those theoretical virtues––such as simplicity, coherence, explanatory power––that are not reducible to empirical strength or adequacy? The answers to these questions rely strongly on the pragmatics of scientific inquiry, and advocate a ‘Clausewitz doctrine’ of experimentation as a continuation of theorizing by other means.Less
Scientific theories do much more than answer empirical questions. This can be understood along empiricist lines only if those other aspects are instrumental for the pursuit of empirical strength and adequacy, or serving other aims subordinate to these. This chapter accordingly addresses four main questions: (1) Does the rejection of realism lead to a self‐defeating scepticism? (2) Are scientific methodology and experimental design intelligible on any but a realist interpretation of science? (3) Is the ideal of the unity of science, or even the practice of using distinct theories in conjunction, intelligent on an empiricist view? (4) What sense can an empiricist position accord to those theoretical virtues––such as simplicity, coherence, explanatory power––that are not reducible to empirical strength or adequacy? The answers to these questions rely strongly on the pragmatics of scientific inquiry, and advocate a ‘Clausewitz doctrine’ of experimentation as a continuation of theorizing by other means.
J. D. Trout
- Published in print:
- 1998
- Published Online:
- February 2006
- ISBN:
- 9780195107661
- eISBN:
- 9780199786152
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0195107667.003.0003
- Subject:
- Philosophy, Metaphysics/Epistemology
The sort of realism supported by statistical principles and experimental design is a thin one. Populations or their members have a real value independent of attempts to measure them, and independent ...
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The sort of realism supported by statistical principles and experimental design is a thin one. Populations or their members have a real value independent of attempts to measure them, and independent of observations concerning them. As a result, the realist can invoke these unobserved, real values in their explanations of observed behavior or correlations. That there could be a general argument for realism required to account for the reliability of specific statistical principles is a novel contention. Although it is a familiar idea that the theoretical considerations raised in good experimental design require a realist interpretation, no such presumption in favor of realism has accompanied the treatment of general statistical principles. Robust realism, by contrast, holds that the approximate truth of mature scientific theories is the best explanation for their success. This strong version of realism has only mature sciences as its subject matter, and the evidence for it in the social and behavioral sciences is uneven.Less
The sort of realism supported by statistical principles and experimental design is a thin one. Populations or their members have a real value independent of attempts to measure them, and independent of observations concerning them. As a result, the realist can invoke these unobserved, real values in their explanations of observed behavior or correlations. That there could be a general argument for realism required to account for the reliability of specific statistical principles is a novel contention. Although it is a familiar idea that the theoretical considerations raised in good experimental design require a realist interpretation, no such presumption in favor of realism has accompanied the treatment of general statistical principles. Robust realism, by contrast, holds that the approximate truth of mature scientific theories is the best explanation for their success. This strong version of realism has only mature sciences as its subject matter, and the evidence for it in the social and behavioral sciences is uneven.
R. Paul Thompson
- Published in print:
- 2011
- Published Online:
- September 2011
- ISBN:
- 9780199574131
- eISBN:
- 9780191728921
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199574131.003.0002
- Subject:
- Mathematics, Logic / Computer Science / Mathematical Philosophy
Randomized controlled trials (RCTs) are pervasive in clinical medical research, which stands in stark contrast to other sciences such as physics, chemistry and biology. Most clinical researchers that ...
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Randomized controlled trials (RCTs) are pervasive in clinical medical research, which stands in stark contrast to other sciences such as physics, chemistry and biology. Most clinical researchers that use RCTs regard them as uncovering causal connections. R. A. Fisher best articulated the rationale for this position in 1935. According to Fisher, if randomization, blocking and replication demonstrated a connection between an intervention and an outcome, that connection is causal. This chapter argues that RCTs in clinical medicine do not reveal causal connections. Causal claims in clinical medicine, as in the rest of science, are justified by reference to a robust theory, not RCTs. Part of the argument rests on crucial differences between Fisher's use of RCTs in agriculture and the current use of RCTs in clinical medicine. Two key differences are: the different role of randomization and the legitimacy of assuming homogeneity of the intervention and control entities. A more significant part rests on the integrative power of robust theories; causal attributions are justified by demonstrating that they are, or can be, embedded in a large well-confirm framework. RCTs, by contrast, at best provide isolated input-output connections. A secondary thesis of the paper is that robust theories also allow causal claims to be well-confirmed.Less
Randomized controlled trials (RCTs) are pervasive in clinical medical research, which stands in stark contrast to other sciences such as physics, chemistry and biology. Most clinical researchers that use RCTs regard them as uncovering causal connections. R. A. Fisher best articulated the rationale for this position in 1935. According to Fisher, if randomization, blocking and replication demonstrated a connection between an intervention and an outcome, that connection is causal. This chapter argues that RCTs in clinical medicine do not reveal causal connections. Causal claims in clinical medicine, as in the rest of science, are justified by reference to a robust theory, not RCTs. Part of the argument rests on crucial differences between Fisher's use of RCTs in agriculture and the current use of RCTs in clinical medicine. Two key differences are: the different role of randomization and the legitimacy of assuming homogeneity of the intervention and control entities. A more significant part rests on the integrative power of robust theories; causal attributions are justified by demonstrating that they are, or can be, embedded in a large well-confirm framework. RCTs, by contrast, at best provide isolated input-output connections. A secondary thesis of the paper is that robust theories also allow causal claims to be well-confirmed.
