JB.logreg_m: A complete table for multipy logistic regression analysis for
In SophiaJia/Jsurvformat: Survival analysis output format for clinical research

Description Usage Arguments Value Examples

JB.logreg_m output the table with general logistic regression analysis result with HR (95% Confidence Interval),P value. This function only change the format of the output. Note the difference with JS.crisk, however the usage is the same

1	JB.logreg_m(xvar, yvar, name, factorNY = FALSE)

`xvar`	A matrix of independent variable
`yvar`	Dependent variable range(0,1)
`name`	A vertor of independent variable name

A formated output including OR(95% Confidence Intervals), P value.

X      <- cbind(D$mutation,D$group2_1, D$group2_2 , D$age_ge60, D$comor_m, D$transplant_type, D$donor_m2, D$cellsource_m, D$diseasestat_m2)
Gnames <- c('SRSF2/U2FA1(WT vs Mutation)', 'Disease(AML vs MPN)', 'Disease(AML vs MDS or MDS/MPN)',
           'Age(< 60 vs > 60)', 'Comorbidity(Low vs Intern vs High)','Transplant ( Myeloblative vs Reduced Intensity)',
           'Donor(Sib/Related vs Unrelated)','Cell Source(BM vs PSC vs Cord)','Disease status(Relapse/Refrac or Untreated vs CR/NR/PR)')
JB.logreg_m(X, D$aGVHD_1Y, Gnames)