sts (version 1.4)

estimateRegns: Regression Table Estimation

Description

Estimates regression tables for prevalence and sentiment/discourse.

Usage

estimateRegns(object, prevalence_sentiment, corpus)

Value

a list of tables with regression coefficient estimates. The first num-topic elements pertain to prevalence; the latter num-topic elements pertain to sentiment-discourse.

Arguments

object

an sts object

prevalence_sentiment

A formula object with no response variable or a design matrix with the covariates. If a formula, the variables must be contained in corpus$meta.

corpus

The document term matrix to be modeled in a sparse term count matrix with one row per document and one column per term. The object must be a list of with each element corresponding to a document. Each document is represented as an integer matrix with two rows, and columns equal to the number of unique vocabulary words in the document. The first row contains the 1-indexed vocabulary entry and the second row contains the number of times that term appears. This is the same format in the stm package.

Details

Estimate Gamma coefficients (along with standard errors, p-values, etc.) to assess how document-level meta-data determine prevalence and sentiment/discourse

Examples

# \donttest{
library("tm"); library("stm"); library("sts")
temp<-textProcessor(documents=gadarian$open.ended.response,
metadata=gadarian, verbose = FALSE)
out <- prepDocuments(temp$documents, temp$vocab, temp$meta, verbose = FALSE)
out$meta$noTreatment <- ifelse(out$meta$treatment == 1, -1, 1)
## low max iteration number just for testing
sts_estimate <- sts(~ treatment*pid_rep, ~ noTreatment, out, K = 3, maxIter = 2)
regns <- estimateRegns(sts_estimate, ~treatment*pid_rep, out)
printRegnTables(x = regns)
# }