Assumptions of Linear Regression - Statistics Solutions - linear regression results rule of thumb

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linear regression results rule of thumb - Linear Regression in SPSS - A Simple Example


You are here: Home Regression Multiple Linear Regression Tutorials Linear Regression in SPSS – A Simple Example A company wants to know how job performance relates to IQ, motivation and social support. They collect data on 60 employees, resulting in job_performance.sav.Part of . The number of subjects per variable required in linear regression analyses. In the former class, Green described a rule, attributable to Marks, that specifies a minimum of 200 subjects for any regression analysis. In the latter class, Green described a rule, attributable to Tabachnick and Fidell, who suggested (with what Green described as Cited by: 324.

My “rules-of-thumb” for choosing which regression to use are as follows: For situations where the X-parameter is controlled, as in making-up standards for instrument calibration or doing laboratory experiments where only one variable is changed, then the standard model-I regressions are required. Objective: The suggested ‘‘two subjects per variable’’ (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression.