Quasi-experimentation: Design & Analysis Issues for Field SettingsHoughton Mifflin, 1979 - 405 halaman This book presents some quasi-experimental designs and design features that can be used in many social research settings. The designs serve to probe causal hypotheses about a wide variety of substantive issues in both basic and applied research. Each design is assessed in terms of four types of validity, with special stress on internal validity. Although general conclusions are drawn about the strengths and limitations of each design, emphasis is also placed on the fact that the relevant threats to valid inference are specific to each research setting. Consequently, a threat that is usually associated with a particular design need not invariably be associated with that design. |
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Causal Inference and the Language of Experimentation | 1 |
Validity | 37 |
Nonequivalent Control Group Designs | 95 |
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ACF and PACF ANCOVA ARIMA model attrition Autocorrelations of lags bias biased blocking Box-Jenkins breathalyser Campbell causal inference causal relationship cause chapter coefficients cohort component construct validity correlation covariate cross-correlation cross-lagged cutting point dependent variable differenced differential discussion example expected experimental group Figure hypothesis implemented increase individuals interaction internal validity intervention irrelevant IXXX IXXXX manipulation matching mean measurement error ment multiple nonequivalent group design observations outcome parameters Partial autocorrelations particular path coefficients pattern persons plausible population possible posttest scores predicted pretest and posttest pretest scores pretest-posttest problem procedure quasi-experiment random assignment randomized experiment regression lines reliability respondents sample SD 2 SD seasonal seasonal lags selection differences Sesame Street settings specified statistical conclusion validity statistically significant t-statistic theory threats to internal tion transfer function treatment effect estimate treatment group trend variance white noise