jointest (version 1.0)

combine-methods: Nonparametric combination of jointest objects

Description

Methods for combining jointest objects.

combine combines the tests derived from multiverse models.

combine_contrasts combines the tests derived from the contrasts of a factor variable to get a global test for the factor (i.e. categorical predictor). It has strong analogies with ANOVA test.

Usage

combine(mods, comb_funct = "maxT", by = NULL, by_list=NULL, tail = 0)
combine_contrasts(mods, comb_funct = "Mahalanobis", tail = 0)

Value

The function returns a jointest-object.

Arguments

mods

a jointest object.

comb_funct

combining function to be used. Several functions are implemented: "mean", "median", "Fisher", "Liptak", (equal to) "Stoufer", "Tippet", (equal to) "minp", "maxT", "Mahalanobis". Alternatively it can be a custom function that has a Tspace matrix as input. For combine the default is comb_funct="maxT", while for combines_contrasts the default is comb_funct="Mahalanobis".

by

if NULL (default), it combines all test statistics. If a characters, it refers to the column's name of summary_table (and printed by something like summary(mods)). The elements with the same value will be combined. If by is a vector, the values are defined by row-wise concatenation of the values of the columns in by. The argument is inactive if by_list is not NULL.

by_list

NULL (default) or a list of vectors. For each vector of the list it combines test statistics with position given by the element of the vector. If the vectors in the list are characters, these refer to names(mods$Tspace).

tail

direction of the alternative hypothesis. It can be "two.sided" (or 0, the default), "less" (or -1) or "greater" (or +1).

Examples

#First example
library(jointest)
set.seed(123)

#Simulate data
n=20
D=data.frame(X=rnorm(n),Z1=rnorm(n),Z2=rnorm(n))
D$Y=D$Z1+D$X+rnorm(n)

# Run four glms abd combine it in a list
mod1=glm(Y~X+Z1+Z2,data=D)
mod2=glm(Y~X+poly(Z1,2)+Z2,data=D)
mod3=glm(Y~X+poly(Z1,2)+poly(Z2,2),data=D)
mod4=glm(Y~X+Z1+poly(Z2,2),data=D)
mods=list(mod1=mod1,mod2=mod2,mod3=mod3,mod4=mod4)

# Let us analyze the tests related to coefficient "X" and combine them
res=join_flipscores(mods,n_flips = 5000, seed = 1, tested_coeffs = "X")
summary(combine(res))
# Second (continued) example
# flipscores jointly on all models and all coefficients
res=join_flipscores(mods,n_flips = 2000)
summary(combine(res))
summary(combine(res, by="Model"))
summary(combine(res, by="Coeff"))
res2=combine_contrasts(res)
summary(res2)
#custom combinations:
coeffs=c("(Intercept)","X","Z1","Z2")
coeffs_ids=lapply(coeffs,grep,res2$summary_table$Coeff)
names(coeffs_ids)=coeffs
summary(combine(res2,by_list =   coeffs_ids))