The goal of phackr is to produce excel sheets showing multivariate significance for several dependent variables across as many covariates as specified. The function currently only supports ordered logistic regression models. The future plan for the package is to allow specification of several interchangeable covariates to output to multiple excel sheets.
You can install the development version from github with:
library(devtools)
install_github("willdebras/phackr")library(phackr)
library(tibble)You can use the phackr_setup() function to setup a survey object
library(rio)
data <- import("full_data.dta")
survey_data <- phackr_setup(data = data, weight = "finalwt", caseid = "su_id")Once it is setup, you can use the phackr() function to actually
produce the tables.
sheet1 <- phackr(data = survey_data,
dvs = c("factor(trade1a)", "factor(trade1b)", "factor(trade1c)", "factor(trade1d)", "factor(trade1e)", "factor(trade1f)", "factor(trade1g)", "factor(trade2)", "factor(trade3a)", "factor(trade3b)", "factor(trade3c)"),
demos = c("urban", "marital", "agegrp", "education", "hhincome", "empstatus", "gender"))
library(knitr)
kable(sheet1)| factor(trade1a) | factor(trade1b) | factor(trade1c) | factor(trade1d) | factor(trade1e) | factor(trade1f) | factor(trade1g) | factor(trade2) | factor(trade3a) | factor(trade3b) | factor(trade3c) | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| urban | - | + | |||||||||
| marital | - | - | + | ||||||||
| agegrp | |||||||||||
| education | - | + | + | - | |||||||
| hhincome | - | ||||||||||
| empstatus | |||||||||||
| gender | - | + | + |