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selecting the regression method, confounding variables are viewed as covariates , stop removing variables when criterion is reached, when criterion is reached (e.g., absence of statistically significant increase in r^2), atheoretical, take advantage of chance, results are cross validated on a new sample, order of etnry is determiend by a selction algorithm, can't determine causality, describe the relationships between iv and dvs, variance above and beyond previous variables , large sample size (40 1) subjects precitor variables, tend to be overfit, maximize r^2 while minimizing predictor variables, stepwise regression (setwise), testing theoretical model, cochen and cohen (1983), confounding the analysis, options, ivs w highest correlation to dv (highest first order correlation w criterion) are entered first, forward selection, can assess the multipe correlation between a dv and a group of ivs and to assess the impact of each iv, controlling for the otehrs, important related to dv, researcher is removed from analysis', prediction, all ivs are entered into regression in 1 step group, simultaneous entry (standard method), research goal is primarily to predict criterion, all variables are entered at outset, backward elimination, selecting the regression method, hierarchical regression