Why does generalizing a multiple regression equation to another sample tend to produce a lower R² in the second sample? A) the internal validity of nonexperimental methods is lower than for experimental methods B) the external validity of nonexperimental methods is lower than for experimental methods C) the regression equation assumes that data are free from measurement error, so any error present in sample 1 will likely be different from error in sample 2, and in turn, decreasing the amount of correspondence between sample 1 regression weights and sample 2 data. D) the regression equation assumes that data are free from sampling error, so any error present in sample 1 will make the regression weights artificially high, and in turn, sample 2 reveals variable weights that are more accurate reflections of reality

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Quizplus · Accepted Answer

Generalizing a regression equation assumes that the same variables are present in both sample 1 and sample 2, and that the relationships between variables are consistent across both samples. However, measurement error can affect the variables differently in each sample, which decreases the amount of correspondence between the regression weights from sample 1 and the data in sample 2. Therefore, the R² tends to be lower in the second sample.

Why Does Generalizing a Multiple Regression Equation to Another Sample