regression.model.functions {kyotil}R Documentation

Regression Model Functions

Description

getFormattedSummary prints a table of regression coefficient estimates and standard errors.

Usage


getFormattedSummary(fits, type = 2, est.digits = 2, se.digits = 2, robust,
         random = FALSE, VE = FALSE, to.trim = FALSE, rows =
         NULL, coef.direct = FALSE, ...)

getVarComponent(object, ...)

getFixedEf(object, ...)

risk.cal(risk, binary.outcome, weights = NULL, ngroups = NULL, 
    cuts = NULL, main = "", add = FALSE, show.emp.risk = TRUE, 
    lcol = 2, ylim = NULL, scale = c("logit", "risk"))
interaction.table(fit, v1, v2, v1.type = "continuous", v2.type = "continuous",
logistic.regression = TRUE)


## S3 method for class 'coxph'
getFixedEf(object, exp=FALSE,robust=FALSE, ...)

## S3 method for class 'gam'
getFixedEf(object, ...)

## S3 method for class 'gee'
getFixedEf(object, exp = FALSE, ...)

## S3 method for class 'geese'
getFixedEf(object, ...)
## S3 method for class 'tps'
getFixedEf(object, exp=FALSE, robust=TRUE, ...)

## S3 method for class 'glm'
 getFixedEf(object, exp = FALSE, robust = TRUE, ret.robcov = FALSE, 
    ...)  


## S3 method for class 'inla'
getFixedEf(object, ...)

## S3 method for class 'lm'
getFixedEf(object, ...)

## S3 method for class 'lme'
getFixedEf(object, ...)

## S3 method for class 'logistf'
getFixedEf(object, exp = FALSE, ...)

## S3 method for class 'matrix'
getFixedEf(object, ...)

## S3 method for class 'MIresult'
getFixedEf(object, ...)

## S3 method for class 'hyperpar.inla'
getVarComponent(object, transformation = NULL, ...)

## S3 method for class 'matrix'
getVarComponent(object, ...)

## S3 method for class 'geese'
coef(object, ...)
## S3 method for class 'tps'
coef(object, ...)

## S3 method for class 'geese'
predict(object, x, ...)
## S3 method for class 'tps'
predict(object, newdata = NULL, type = c("link", "response"), ...)

## S3 method for class 'geese'
residuals(object, y, x,...)

## S3 method for class 'geese'
vcov(object, ...)
## S3 method for class 'tps'
vcov(object, robust, ...)

## S3 method for class 'logistf'
vcov(object, ...)

Arguments

...
object
fit
coef.direct
robust

Boolean, whether to return robust variance estimate

exp
cuts
ret.robcov
fits
type
est.digits
se.digits
random
VE
transformation
weights
v1
v2
v1.type
v2.type
logistic.regression
newdata
x
y
to.trim
rows
risk
binary.outcome
ngroups
main
add
show.emp.risk
lcol
ylim
scale

Details

getFormattedSummary: from a list of fits, say lmer, inla fits, return formatted summary controlled by "type". For a matrix, return Monte Carlo variance random=TRUE returns variance components type=1: est type=2: est (se) type=3: est (2.5 percent, 97.5 percent) type=4: est se

getFixedEf returns a matrix, first column coef, second column se,

getFixedEf.matrix used to get mean and sd from a jags or winbugs sample, getVarComponent.matrix and getFixedEf.matrix do the same thing. Each column of samples is a variable

interaction.table expects coef and vcov to work with fit.

Examples


## Annette Dobson (1990) "An Introduction to Generalized Linear Models".
## Page 9: Plant Weight Data.
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
glm.D9 <- glm(weight ~ group)
getFormattedSummary (list(lm.D9, glm.D9), robust=FALSE)


[Package kyotil version 2018.10-17 Index]