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Causation and Experimental Design - SAGE Publications Inc

106 Chapter 5 Causation andExperimental DesignCausal ExplanationWhat causes What?AssociationTime OrderNonspuriousnessMechanismContextWhy Experiment?What If a True Experiment Isn tPossible?Nonequivalent Control Group DesignsBefore-and-After DesignsEx Post Facto Control Group DesignsWhat Are the Threats to Validity inExperiments?Threats to Internal Causal ValidityNoncomparable GroupsEndogenous ChangeHistoryContaminationTreatment MisidentificationGeneralizabilitySample GeneralizabilityCross-PopulationGenerali zabilityInteraction of Testing andTreatmentHow Do Experimenters Protect TheirSubjects?

dentifying causes—figuring out why things happen—is the goal of most social science research. Unfortunately, valid explanations of the causes of social ... and erratic discipline as the means by which poverty and delinquency are connected (Sampson & Laub, 1994). In this way, figuring out some aspects of the process by

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Transcription of Causation and Experimental Design - SAGE Publications Inc

1 106 Chapter 5 Causation andExperimental DesignCausal ExplanationWhat causes What?AssociationTime OrderNonspuriousnessMechanismContextWhy Experiment?What If a True Experiment Isn tPossible?Nonequivalent Control Group DesignsBefore-and-After DesignsEx Post Facto Control Group DesignsWhat Are the Threats to Validity inExperiments?Threats to Internal Causal ValidityNoncomparable GroupsEndogenous ChangeHistoryContaminationTreatment MisidentificationGeneralizabilitySample GeneralizabilityCross-PopulationGenerali zabilityInteraction of Testing andTreatmentHow Do Experimenters Protect TheirSubjects?

2 DeceptionSelective Distribution of BenefitsConclusionIdentifying causes figuring out why things happen is the goal of mostsocial science research. Unfortunately, valid explanations of the causes of socialphenomena do not come easily. Why did the homicide rate in the United Statesdrop for 15 years and then start to rise in 1999 (Butterfield, 2000:12)? Was itbecause of changes in the style of policing (Radin, 1997:B7) or because of chang-ing attitudes among young people (Butterfield, 1996a)?

3 Was it due to variation 1/9/2006 2:23 PM Page 106patterns of drug use (Krauss, 1996) or to tougher prison sentences (Butterfield,1996a) or to more stringent handgun regulations (Butterfield, 1996b)? Did betteremergency medical procedures result in higher survival rates for victims (Ramirez,2002)? If we are to evaluate these alternative explanations we must Design ourresearch strategies chapter considers the meaning of Causation , the criteria for achieving causallyvalid explanations, the ways in which Experimental and quasi- Experimental researchdesigns seek to meet these criteria, and the difficulties that can sometimes result ininvalid conclusions.

4 By the end of the chapter, you should have a good grasp of themeaning of Causation and the logic of Experimental Design . Most social research,both academic and applied, uses data collection methods other than because Experimental designs are the best way to evaluate causal hypothe-ses, a better understanding of them will help you to be aware of the strengths andweaknesses of other research designs that we will consider in subsequent EXPLANATIONA cause is an explanation for some characteristic, attitude, or behavior of groups,individuals, or other entities (such as families, organizations.)

5 Or cities) or for example, Sherman and Berk (1984) conducted a study to determine whetheradults who were accused of a domestic violence offense would be less likely torepeat the offense if police arrested them rather than just warned them. Their con-clusion that this hypothesis was correct meant that they believed police response hada causal effect on the likelihood of committing another domestic violence effect:The finding that change in one variable leads to changein another variable,ceteris paribus(other things being equal).

6 Example:Individuals arrested for domestic assault tend to commit fewer subsequentassaults than similar individuals who are accused in the same circum-stances but are not specifically, a causal effect is said to occur if variation in the independentvariable is followed by variation in the dependent variable, when all other thingsare equal (ceteris paribus). For instance, we know that for the most part men earnmore income than women do. But is this because they are men or could it be dueto higher levels of education, or to longer tenure in their jobs (with no pregnancybreaks), or is it the kinds of jobs men go into as compared to those that womenchoose?

7 We want to know if men earn more than women,ceteris paribus otherthings (job, tenure, education, etc.) being 5 Causation and Experimental 1/9/2006 2:23 PM Page 107We admit that you can legitimately argue that all other things can t literallybe equal: We can t compare the same people at the same time in exactly the samecircumstances except for the variation in the independent variable (King, Keohane,& Verba, 1994). However, you will see that we can Design research to create condi-tions that are very comparable so that we can isolate the impact of the independentvariable on the dependent causes WHAT?

8 Five criteria should be considered in trying to establish a causal first three criteria are generally considered as requirements for identifyinga causal effect: (1) empirical association, (2) temporal priority of the indepen-dent variable, and (3) nonspuriousness. You must establish these three to claima causal relationship. Evidence that meets the other two criteria (4) identifyinga causal mechanism, and (5) specifying the context in which the effect occurs can considerably strengthen causal designs that allow us to establish these criteria require careful planning,implementation, and analysis.

9 Many times, researchers have to leave one or more ofthe criteria unmet and are left with some important doubts about the validity of theircausal conclusions, or they may even avoid making any causal first criterion for establishing a causal effect is an empirical (or observed)association(sometimes called a correlation) between the independent and depen-dent variables. They must vary together so when one goes up (or down), the othergoes up (or down) at the same time. For example: When cigarette smoking goes up,so does lung cancer.

10 The longer you stay in school, the more money you will makelater in life. Single women are more likely to live in poverty than married income goes up, so does overall health. In all of these cases, a change in anindependent variable correlates, or is associated with, a change in a dependent vari-able. If there is no association, there cannot be a causal relationship. For instance,empirically there seems to be no correlation between the use of the death penalty anda reduction in the rate of serious crime.


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