About Randomized Field Experiments Randomized field experiments allow researchers to scientifically measure the impact of an intervention on a particular outcome of interest. Show
What is a randomized field experiment? In a randomized experiment, a study sample is divided into one group that will receive the intervention being studied (the treatment group) and another group that will not receive the intervention (the control group). For instance, a study sample might consist of all registered voters in a particular city. This sample will then be randomly divided into treatment and control groups. Perhaps 40% of the sample will be on a campaign’s Get-Out-the-Vote (GOTV) mailing list and the other 60% of the sample will not receive the GOTV mailings. The outcome measured –voter turnout– can then be compared in the two groups. The difference in turnout will reflect the effectiveness of the intervention. What does random assignment mean? The key to randomized experimental research design is in the random assignment of study subjects – for example, individual voters, precincts, media markets or some other group – into treatment or control groups. Randomization has a very specific meaning in this context. It does not refer to haphazard or casual choosing of some and not others. Randomization in this context means that care is taken to ensure that no pattern exists between the assignment of subjects into groups and any characteristics of those subjects. Every subject is as likely as any other to be assigned to the treatment (or control) group. Randomization is generally achieved by employing a computer program containing a random number generator. Randomization procedures differ based upon the research design of the experiment. Individuals or groups may be randomly assigned to treatment or control groups. Some research designs stratify subjects by geographic, demographic or other factors prior to random assignment in order to maximize the statistical power of the estimated effect of the treatment (e.g., GOTV intervention). Information about the randomization procedure is included in each experiment summary on the site. What are the advantages of randomized experimental designs? Randomized experimental design yields the most accurate analysis of the effect of an intervention (e.g., a voter mobilization phone drive or a visit from a GOTV canvasser, on voter behavior). By randomly assigning subjects to be in the group that receives the treatment or to be in the control group, researchers can measure the effect of the mobilization method regardless of other factors that may make some people or groups more likely to participate in the political process. To provide a simple example, say we are testing the effectiveness of a voter education program on high school seniors. If we allow students from the class to volunteer to participate in the program, and we then compare the volunteers’ voting behavior against those who did not participate, our results will reflect something other than the effects of the voter education intervention. This is because there are, no doubt, qualities about those volunteers that make them different from students who do not volunteer. And, most important for our work, those differences may very well correlate with propensity to vote. Instead of letting students self-select, or even letting teachers select students (as teachers may have biases in who they choose), we could randomly assign all students in a given class to be in either a treatment or control group. This would ensure that those in the treatment and control groups differ solely due to chance. The value of randomization may also be seen in the use of walk lists for door-to-door canvassers. If canvassers choose which houses they will go to and which they will skip, they may choose houses that seem more inviting or they may choose houses that are placed closely together rather than those that are more spread out. These differences could conceivably correlate with voter turnout. Or if house numbers are chosen by selecting those on the first half of a ten page list, they may be clustered in neighborhoods that differ in important ways from neighborhoods in the second half of the list. Random assignment controls for both known and unknown variables that can creep in with other selection processes to confound analyses. Randomized experimental design is a powerful tool for drawing valid inferences about cause and effect. The use of randomized experimental design should allow a degree of certainty that the research findings cited in studies that employ this methodology reflect the effects of the interventions being measured and not some other underlying variable or variables. Experimental Designs The Uniqueness of Experimental Methodology Experimental Control Determination of Causality Internal versus External Validity Another advantage of a well-designed experimental method is its high level of internal validity. A design that has high internal validity allows you to conclude that a particular variable is the direct cause of a particular outcome. In contrast external validity is often seen as a challenge for experimental work. External validity is the degree to which conclusions drawn from a particular set of results can be generalized to other samples and situations. The sample in a particular experiment may not represent the larger population of interest, and the experimental situation may not resemble the real-world context that it is designed to model because of its artificiality. The concern around artificiality is controversial and not shared by everyone who does psychological research. Key Constructs of Experimental Methods Independent and Dependent Variables Experimental
and Control Groups Placebo Effect Random Assignment Types of Experimental Designs Between-Subjects Designs Advantages of Between-Subjects Designs Disadvantages of
Between-Subjects Designs Within-Subjects Designs Advantages of Within-Subjects Designs Disadvantages of Within-Subjects Designs Matched Group Designs Advantages of Matched Group Designs Disadvantages of Matched Group Designs Confounding Factors and Extraneous Variables Participant Characteristics The Hawthorne Effect Demand Characteristics Other Confounds Strategies for Dealing with Confounds Hold Potential Confounding Variables Constant Vary Test Items and Tasks Use Blind and Double-Blind Designs Statistically Control for Variables that Can’t be
Experimentally Controlled Use Randomization and Counterbalancing Ceiling and Floor
Effects What Steele and Aronson Found Ethical Considerations in Experimental Design Placebo/Control Group and Denial of Treatment Confederates and Deceit What effect does random assignment of subjects to experimental and control groups have?Researchers randomly assign participants in a study to either the experimental group or the control group. Dividing the participants randomly reduces group differences, thereby reducing the possibility that confounding factors will influence the results.
Which type of experimental design has a control group and random assignment to groups?This is also called the classic controlled experimental design, and the randomized pre-test/post-test design because it: 1) Controls the assignment of subjects to experimental (treatment) and control groups through the use of a table of random numbers.
Why is the random assignment of individuals to experimental and control groups important?Why is the random assignment of individuals to experimental and control groups important for an experiment? It allows the experiment to better represent the population as a whole. differences between a group of experimental subjects and the population as a whole.
Which type of research involves random assignment and a control condition?Random assignment to conditions in between-subjects experiments or to orders of conditions in within-subjects experiments is a fundamental element of experimental research. Its purpose is to control extraneous variables so that they do not become confounding variables.
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