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The validity of inferences stemming from empirical research in industrial and organizational psychology and allied disciplines is a function of a number of factors, including research design. Research design has to do with the plan, structure, or blueprint for a study. The literature indicates that among the components of such a plan are (a) the experimental design type (i.e., randomized experiment, quasi-experiment, and nonexperiment); (b) the study setting (e.g., created for the purpose of doing research); (c) the numbers and types of study participants; (d) the way in which the variables considered by the study are operationally defined; and (e) the techniques that will be used to analyze the data produced by the study. The focus here is on the randomized experiment. It differs in important ways from both nonexperimental and quasi-experimental design types.

Prior to considering the nature of randomized experiments, we consider several issues concerning the validity of inferences stemming from empirical research. Note that the same issues apply not only to randomized experiments but also to quasi-experiments and nonexperiments.

Factors Affecting the Validity of Research-Based Inferences

The overall correctness of inferences (e.g., research-based conclusions, recommendations for practice) stemming from a study is a function of its design and the manner in which it is actually conducted. Four facets of validity are critical: construct validity, statistical conclusion validity, internal validity, and external validity, as noted by Thomas Cook and Donald Campbell in 1979, and by W. R. Shadish, Cook, and Campbell in 2002.

Construct Validity

Construct validity is a function of the degree of correspondence between the constructs dealt with by a study and their realizations. It has to do with not only the operational definitions of variables (e.g., manipulations, measures), but also the empirical realizations of other features of a study (e.g., types of participants, research settings). Construct validity inferences are threatened by a number of factors, including inadequate preoperational definitions of constructs, study procedures that lead participants to guess a study's hypotheses and behave in ways that confirm them, operational definitions that underrepresent focal constructs, and a lack of correspondence between the type of participants in a study and the way the participants are labeled by a researcher.

Statistical Conclusion Validity

Statistical conclusion validity has to do with the correctness of inferences about relations between variables that stem from the results of statistical tests. Among the factors that threaten this facet of validity are testing statistical hypotheses with data that violate relevant assumptions (e.g., homogeneity of variance), implementing treatments unreliably within study conditions, conducting research in settings having random irrelevancies (e.g., fluctuations in noise, temperature, illumination), and sampling too few units (e.g., participants) to provide for adequate statistical power in hypothesis testing.

Internal Validity

Internal validity is the degree to which inferences about causal connections between variables are correct. Among the factors that detract from the validity of such inferences are history, maturation, instrumentation, testing, selection, and mortality.

External Validity

External validity deals with the correctness of inferences about the generalizability of a study's findings to and across populations of settings, participants, time periods, and so forth. External validity is threatened by such factors as interactions between settings and treatments, interactions between history and treatments, and interactions between selection and treatments.

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