Also, based on stepwise regression, testing the orientation or core domain on either the MMSE or MoCA may help distinguish HC from MCI cases, though this needs to be further evaluated in other samples.
A stepwise regression run and a subsequent ANOVA test show that dip, convection, and their product are the most significant factors: E = beta_{0} + beta_{D} D + beta_{C} C + beta_{CD} CD (3)where C is a boolean variable indicating whether the simulation was run with natural convection initialization, D is dip in degrees, and E is gross energy output in joules; β's are the regression coefficients.
We used the likelihood ratio test in a backward stepwise regression to test for interaction.
Nominal data were compared by Pearson chi-square test, Fisher exact test or multiple forward stepwise logistic regression test when appropriate.
Factors reaching significance of univariate analysis were entered in a multivariate analysis using the Cox stepwise logistic regression test to investigate the independence of the various risk factors.
QSPPBR models were derived after variable selection by genetic algorithm followed by stepwise regression and tested by cross- and external validation.
Briefly, composite interval mapping (CIM) was performed in ZmapQTL with a 10 cM window and a maximum of five background cofactors identified using SRmapQTL with forward/backward stepwise regression, and tests were performed at 2 cM intervals.
Data were analyzed by independent t-student's, chi-square, Pearson correlation, and stepwise multiple regression tests.
Associations between concentrations of proteins and U-Cd were assessed in stepwise regression analyses by testing as potential predictors age, BMI, U-Cd, B-Pb, U-Zn, current smoking, and the number of pack-years, which were introduced in the models as dummy variables (pack-years > 1-15 and > 15).
Stepwise regression was used to test the relationship between the physico-chemical parameters and biological variables; the observed (r) values were then compared to the table values at P < 0.05 level of significance, whereas abundance of phytoplankton was analyzed using percentage.
For CDR and Braak stage analyses, stepwise regression was used to test linear association of gene expression, controlling for the same covariates as in ANCOVA.
