Gain Score in Data Analysis
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How to use gain score in data analysis
Transcript of Gain Score in Data Analysis
Gain Score ?Gain Score ?Measurement IssuesMeasurement Issues Ceiling effectCeiling effect SkewnessSkewness Reliability issue Reliability issue Statistical IssuesStatistical Issues IndependenceIndependence Sample sizeSample size Standard errorStandard error Type II error ( null hypothesis is false but fail to reject)Type II error ( null hypothesis is false but fail to reject) Statistical Power (the probability of correctly rejecting null hypothesis) Statistical Power (the probability of correctly rejecting null hypothesis) (increase sample size, increase effect size, increase alpha –(increase sample size, increase effect size, increase alpha –αα decrease decrease variance/standard deviation) variance/standard deviation) Equivalent control group or non-equivalent control groupEquivalent control group or non-equivalent control group Statistical control – ANCOVA (Statistical control – ANCOVA (adjust the post-test score for the measured pretest adjust the post-test score for the measured pretest scores or removes pretest differences between the treatment and control group)scores or removes pretest differences between the treatment and control group)
Research Design IssuesResearch Design Issues Experimental / quasi-experimental designExperimental / quasi-experimental design Sample sizeSample size Standard errorStandard error ControlControl Extraneous factorsExtraneous factors
Solutions? – Solutions? – posttest score, ANCOVA,posttest score, ANCOVA, Repeated MeasuresRepeated Measures
