Extracts p-values

Description

Takes a list of fitted models (lm objects) and obtains the p-values associated with each fit.

Usage

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pvalmat(lst,regressors)

Arguments

lst

list of lm objects.

regressors

character vector. Names of the coefficients for which p-values are extracted.

Details

Simple wrapper function that returns p-values extracted from summary(lm).

The coefficient names corresponding to the p-values to be extracted are matched based on their names in rownames(summary(lst[[i]])$coef).

Value

pvalm

numeric matrix. Matrix of extracted p-values with one row for each model in the list and one column for each targeted coefficient.

Author(s)

Alexandre Kuhn alexandre.m.kuhn@gmail.com

See Also

coefmat.

Examples

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## Load example expression data (variable "expression")
## and phenotype data (variable "groups")
data("example")

## Four cell population-specific reference signals
neuron_probesets <- list(c("221805_at", "221801_x_at", "221916_at"),
		"201313_at", "210040_at", "205737_at", "210432_s_at")
neuron_reference <- marker(expression, neuron_probesets)

astro_probesets <- list("203540_at",c("210068_s_at","210906_x_at"),
		"201667_at")
astro_reference <- marker(expression, astro_probesets)

oligo_probesets <- list(c("211836_s_at","214650_x_at"),"216617_s_at",
		"207659_s_at",c("207323_s_at","209072_at"))
oligo_reference <- marker(expression, oligo_probesets)

micro_probesets <- list("204192_at", "203416_at")
micro_reference <- marker(expression, micro_probesets)

## Stepwise model selection for 2 transcripts (202429_s_at and
## 200850_s_at) and focusing on control samples (i.e. groups == 0)
lmlist <- swlm(expression[c("202429_s_at", "200850_s_at"),],
		subset = which(groups == 0),
		upper = formula(~neuron_reference + astro_reference +
			oligo_reference + micro_reference))

pvalmat(lmlist, c("(Intercept)", "neuron_reference", "astro_reference",
		"oligo_reference", "micro_reference"))