kyotil (version 2015.11-13)

regression.model.functions: Regression Model Functions

Description

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

Usage

getFormattedSummary(fits, type = 1, est.digits = 2, se.digits = 2, random = FALSE,  VE=FALSE, ...)
getVarComponent(object, ...)
getFixedEf(object, ...)
"getFixedEf"(object, exp=FALSE,robust=FALSE, ...)
"getFixedEf"(object, ...)
"getFixedEf"(object, ...)
"getFixedEf"(object, ...)
"getFixedEf" (object, exp=FALSE, robust=TRUE, ...) 

"getFixedEf"(object, ...)
"getFixedEf"(object, ...)
"getFixedEf"(object, ...)
"getFixedEf"(object, exp = FALSE, ...)
"getFixedEf"(object, ...)
"getFixedEf"(object, ...)
"getVarComponent"(object, transformation = NULL, ...)
"getVarComponent"(object, ...)
interaction.table(fit, v1, v2, v1.type = "continuous", v2.type = "continuous",  logistic.regression = TRUE)
"coef"(object, ...)
"predict"(object, x, ...)
"residuals"(object, y, x,...)
"vcov"(object, ...)
"vcov"(object, ...)

Arguments

...

object

fit

robust

Boolean, whether to return robust variance estimate

exp

fits

type

est.digits

se.digits

random

VE

transformation

v1

v2

v1.type

v2.type

logistic.regression

x

y

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

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)