A study is valid if its measures actually measure what they claim to, and if there are no logical errors in drawing conclusions from the data. There are a great many labels for different types of validity, but they all have to do with threats and biases which would undermine the meaningfulness of research. Be less concerned about defining and differentiating the types of validity. Researchers disagree on the definitions and types, and yes, they do overlap. Be more concerned about the types of questions the researcher should ask about the validity of research: researchers agree on the importance of the questions.
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Below is the unformatted table of contents.
Table of Contents Overview 5 Historical background 5 Construct validity 7 Convergent validity 7 Internal consistency validity 7 Criteria 8 Common method variance 9 Criterion validity 9 Discriminant validity 12 Correlational Methods 12 Factor Methods 13 AVE Method 13 Structural equation modeling methods 14 Multi-trait multi-method (MTMM) methodologies 14 Content validity 15 Example 16 Internal validity 16 Hawthorne effect (experimenter expectation) 16 Mortality bias 17 Selection bias 17 Evaluation apprehension 17 Compensatory equalization of treatments 17 Compensatory rivalry 17 Resentful demoralization 18 Treatment imitation or diffusion 18 Unintended treatments 18 Instrumentation change 18 History (intervening events) 18 Maturation 19 Mortality 19 Regression toward the mean 19 Test experience 19 Statistical validity 19 Reliability 20 Type I Errors and Statistical Significance 20 Type II Errors and Statistical Power 20 Fallacies of aggregation 21 Strategies 21 Interaction and non-linearity 22 Causal ambiguity 22 Validity Checklist 23 Bibliography 25