Description Usage Arguments Value Examples
Gives sample size necessary to demonstrate that
coefficient in model for given predictor is equal to its
given value (rather than equal to zero) for a given level
of power and significance. 
 
 Also number of events
(smaller of outcome y=0 and outcome y=1) per
predictor. 
 
 Uses different methods depending on
whether model has one binomial, one continuous or
multiple predictors.
| 1 | 
| x | A logistic regression model of class  | 
| alpha | significance level α for null-hypothesis significance test | 
| beta | power β for null-hypothesis significance test | 
| coeff | Name of predictor (coefficient) in model to be tested | 
A list of:
| res | Result: Sample size required to show coefficient for predictor is as given in the model rather than 0 | 
| epc | Events per covariate; should be >10 to make meaningful statements about coefficients obtained | 
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | set.seed(1)
### one coefficient, which is binomial
f1 <- genLogiDf(b=1, c=0, n=50)$model
logiSS(f1)
###
### one coefficient, which is continuous
f1 <- genLogiDf(f=0, b=0, c=1, n=50)$model
logiSS(f1, coeff="x1")
###
### binomial coefficient
f1 <- genLogiDf(f=0, b=1, c=1, n=50)$model
logiSS(f1, coeff="x1")
###
### continuous coefficient
f1 <- genLogiDf(f=0, b=1, c=1, n=50)$model
logiSS(f1, coeff="x2")
 | 
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