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  "Title": "Stepwise Variable Selection Procedures for Regression Analysis",
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  "Description": "The stepwise variable selection procedure (with iterations\nbetween the 'forward' and 'backward' steps) can be used to\nobtain the best candidate final regression model in regression\nanalysis. All the relevant covariates are put on the 'variable\nlist' to be selected. The significance levels for entry (SLE)\nand for stay (SLS) are usually set to 0.15 (or larger) for\nbeing conservative. Then, with the aid of substantive\nknowledge, the best candidate final regression model is\nidentified manually by dropping the covariates with p value >\n0.05 one at a time until all regression coefficients are\nsignificantly different from 0 at the chosen alpha level of\n0.05.",
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