PSY230H5 Lecture Notes - Lecture 3: Convergent Validity, Discriminant Validity, Uncorrelated Random Variables
Document Summary
This lecture explains the relation between correlations and causality. This lecture explains the distinction between personality measures and personality constructs (validity) R= p1 + p2 + p3* p4. Reliability coefficients assume that measurement errors are independent. Error at time 1 is unrelated to error at time 2. If error variance is random, reliability coefficients estimate the amount of reliable variance that is not due to random measurement error. Measurement error lowers the "true" correlations between 2 variables. As a rule of thumb, observed effect sizes underestimate true effects. A correlation of 0. 2 (r2= 4%) could be a true correlation of 0. 28 (r2= 8%) if the reliability of the 2 measures were 0. 70. Ruler is a valid measure of height, scale is a valid measure of weight. Statistical definition: the correlation between variance in a measure and variance in the intended construct. Valid variance: the amount of variance in a measure that is explained by the variance in the intended construct.
