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Studocu is not sponsored or endorsed by any college or university PSY-222 Chapter 6 notes Research Methods (Southern New Hampshire University) Studocu is not sponsored or endorsed by any college or university PSY-222 Chapter 6 notes Research Methods (Southern New Hampshire University) Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

PSY-222 Research Methods Spring 2022 / Term 3 Chapter 6 Notes Research Designs for Studying Change Over Time — Multivariate Correlational Research — Correlational studies can provide interesting new information in their own right. Because correlation is not causation, what are the options? Researchers have developed some techniques that enable them to test for the cause. The best of these is experimentation: Instead of measuring both variables, researchers manipulate one variable and measure the other without setting up an experiment. Researchers can use advanced correlational techniques to get closer to making a causal claim. Three techniques: - Longitudinal designs , allow researchers to establish temporal precedence in their data - Multiple - regression analyses , which help researchers rule out certain third-variable explanations - Pattern and parsimony approach , in which the results of a variety of correlational studies all support a single, causal theory — Three Casual Criteria — Three criteria for establishing causation are covariance, temporal precedence, and internal validity. Examine the three criteria: 1. Is there covariance? 2. Is there temporal precedence? 3. Is there internal validity? Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

— Temporal Precedence With Longitudinal Designs — A longitudinal design can provide evidence for temporal precedence by measuring the same variables in the same people at several points in time. Longitudinal research is used in developmental psychology to study changes in a trait or an ability as a person grows older. - Interpreting results from longitudinal designs - Because two or more variables are involved, a multivariate design gives several individual correlations, referred to as cross-sectional correlation, autocorrelations, and cross-lag correlations. - Cross-Sectional correlation is a longitudinal design, a correlation between two variables that are measured at the same time. - Autocorrelations is a longitudinal design, the correlation of one variable with itself is measured at two different times. - Cross-Sectional Correlations and Autocorrelations are generally not the researcher’s primary interests. Cross-lag correlation addresses the directionality problem and helps establish temporal precedence. Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

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— Longitudinal Studies and Three Criteria for Causation — Longitudinal designs can provide some evidence for a causal relationship by means of the three criteria for causation: 1. Covariance . Significant relationships in longitudinal designs help establish covariance. 2. Temporal precedence . A longitudinal design can help researchers make inferences about temporal precedence. 3. Internal validity . When conducted simply—by measuring only the two key variables—longitudinal studies do not help rule out third variables. — Power of Pattern and Parsimony — Longitudinal correlational designs can satisfy the temporal precedence criterion. Researchers investigate causality by using a variety of correlational studies that all point in a single, causal direction. It is hard to overstate the strength of the pattern and parsimony technique. In psychology, researchers commonly use a variety of methods and many studies to explore the strength and limits of a particular research question. Some studies are correlational; some are experimental. Some are on children; others on adults. Some are longitudinal; others are not. — Mediation — Researchers may propose a mediating step between two of the variables. A study does not have to be correlational to include a mediator; experimental studies can also test them. Mediators appear similar to third-variable explanations. Both of them involve multivariate research designs, and researchers use the same statistical tool (multiple regression) to detect them. Third-variable explanation, the proposed third variable is external to the two variables in the original bivariate correlation; it might even be seen as an accident—a problematic “lurking variable” that potentially distracts from the relationship of interest. Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

Researchers use multivariate correlational research, such as longitudinal designs and multiple-regression analyses, to get closer to making causal claims. Longitudinal designs help establish temporal precedence, and multiple-regression analysis helps rule out third variables, thus providing some evidence for internal validity. For any multivariate design, as for any bivariate design, it is appropriate to interrogate the construct validity of the variables in the study by asking how well each variable was measured. Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

— Repeated-Measure Design — A repeated-measures design is a type of within-groups design in which participants are measured on a dependent variable more than once, after exposure to each level of the independent variable. — Concurrent-Measure Design — Concurrent-measures design, participants are exposed to all the levels of an independent variable at roughly the same time, and a single attitudinal or behavioral preference is the dependent variable. Two Independent-Groups Designs and Two Within-Group Designs Independent-Group Design Within-Group Designs Different participants at each level of the independent variable Some participants see all levels of the independent variable Posttest-only design Pretest/posttest design Concurrent-measure design Repeated-Measures design — Six Potential Internal Validity Threats in One-Group, Pretest/Posttest Designs — Several of the internal validity threats apply especially to the really bad experiment but are prevented with a good experimental design. These include maturation threats, history threats, regression threats, attrition threats, testing threats, and instrumentation threats. And the final three threats (observer bias, demand characteristics, and placebo effects) potentially apply to any study. — Three Potential Internal Validity Threats in Any Study — - Observer Bias - Can be a threat to internal validity in almost any study in which there is a behavior-dependent variable. - Demand Characteristics Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

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- Are a problem when participants guess what the study is supposed to be about and change their behavior in the expected direction. - Placebo Effects - Occurs when people receive treatment and really improve but only because the recipients believe they are getting a valid treatment. — Multiphase Iterative Design — Multiphase Iterative Design includes three or more phases, with early ones providing foundational data on which later phases can build. This design has become increasingly common in program evaluation research. 1. Collect baseline quantitative data. 2. Implement an intervention program based on current theories and prior research studies. 3. Collect subsequent qualitative data. 4. Conduct qualitative interviews 5. Make modifications to the intervention program 6. Collect follow-up quantitative and qualitative data. 7. If necessary, repeat steps 5 and 6. Downloaded by Ciara Santos (ciarads027@gmail.com) lOMoARcPSD|21198354

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