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In terms of very rough rules of thumb within the typical context of observational psychological studies involving things like ability tests, attitude scales, personality measures, and so forth, I sometimes think of: n=100 as adequate. n=200 as good. n=400+ as great.
Sep 20, 2022 · R can be squared and interpreted as for r 2, with a rough rule of thumb being .1 (small), .3 (medium), and .5 (large). These R 2 values would indicate 10%, 30%, and 50% of the variance in the DV explained respectively.
Aug 30, 2018 · When taking a rule of thumb with EPV of 10, sample size of 100 is sufficient for eight independent variables. However, results based on the validation for sample size of 100 yielded a lot of bias in the coefficients and Nagelkerke r -squared.
A rule of thumb for the sample size is that regression analysis requires at least 20 cases per independent variable in the analysis, in the simplest case of having just two independent variables that requires n > 40. G*Power can also be used to calculate a more exact, appropriate sample size.
Jan 1, 2017 · least 300 can serve as a simple rule of thumb for providing a sufficient sample size for both MLR and ANCOVA particularly for data that is collected in observational manner such as
Dec 15, 2022 · A rule of thumb is that a 2 unit difference on AICs \((\Delta\text{AIC} = 2)\) is moderate evidence of a difference in the models and more than 4 units \((\Delta\text{AIC}>4)\) is strong evidence of a difference. This is more based on experience than a distinct reason or theoretical result but seems to provide reasonable results in most situations.
Dec 15, 2022 · Basically, large VIFs are bad, with the rule of thumb that values over 5 or 10 are considered “large” values indicating high (over 5) or extreme (over 10) multicollinearity in the model for that particular variable, both indicating that slope coefficients are dangerous to interpret in that model.
