interactionTest (version 1.0)

bootFun: Bootstrapping t-statistics

Description

This function is used to create non-parametrically bootstrapped samples of marginal effects calculated from a model with interaction. The function takes data, model, an index of observations, and identities of the interacted variables and returns a vector of t-statistics corresponding to a single bootstrap deviate for marginal effects in the direction of x.name and z.name.

Usage

bootFun(dat, K, form, fam = "gaussian", x.name, z.name)

Arguments

dat

The data set on which the original model was run

K

Index of observations in dat that will be selected for a particular bootstrap run

form

The formula for the GLM model

fam

The family for the GLM model

x.name

The identity of the first interacted variable

z.name

the identity of the second interacted variable

Value

The bootstrap-t statistics from the function for dy/dx and dy/dz, respectively.

References

Clark, William R., and Matt Golder. 2006. "Rehabilitating Duverger's Theory." Comparative Political Studies 39(6): 679-708.

Esarey, Justin, and Jane Lawrence Sumner. 2015. "Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate." URL: http://jee3.web.rice.edu/interaction-overconfidence.pdf.

Examples

## Not run: 
#  data(legfig)                # Clark and Golder 2006 replication data
# 
#  set.seed(1231124)
# 
#  dat<-subset(legfig, subset=(nineties==1 & old==1))
# 
#  # create bootstrap samples of marginal effects of eneg and logmag on enep1
#  library(boot)
#  boot.t.dist <- boot(data = dat, statistic = bootFun, R = 1000,
#           form=enep1 ~ eneg * logmag + uppertier_eneg + uppertier + proximity1 +
#           proximity1_enpres + enpres, fam="gaussian", x.name="eneg",
#           z.name="logmag")$t
#  boot.t.x.dist<-boot.t.dist[,1:10]
# 
#  # calculate critical t-statistic that sets familywise error rate to 10%
#  # for statistical significance of marginal effect of of eneg at any value of logmag
#  findMultiLims(boot.t.x.dist, type="any", err=0.1)$minimum         # answer: 2.593086
#  ## End(Not run)