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Calculate Log Odds Ratio Between Categories

Source: R/lexical_analysis.R
calculate_log_odds_ratio.Rd

Compares word frequencies between categories using a Laplace-smoothed log frequency ratio, ranked by z-score. Identifies words distinctively used in one category. For an informative-prior weighted log-odds, see calculate_weighted_log_odds().

Usage

calculate_log_odds_ratio(
  dfm_object,
  group_var,
  comparison_mode = c("binary", "one_vs_rest", "pairwise"),
  reference_level = NULL,
  top_n = 10,
  min_count = 5
)

Arguments

dfm_object

A quanteda dfm object

group_var

Character, name of the grouping variable in docvars

comparison_mode

Character, one of "binary", "one_vs_rest", or "pairwise"

  • binary: Compare two categories directly

  • one_vs_rest: Compare each category against all others combined

  • pairwise: Compare all pairs of categories

reference_level

Character, reference category for binary comparison (default: first level)

top_n

Number of top terms per comparison (default: 10)

min_count

Minimum word count to include (default: 5)

Value

Data frame with columns:

  • term: The word/feature

  • category1: First category in comparison

  • category2: Second category in comparison

  • count1: Count in category 1

  • count2: Count in category 2

  • odds1: Odds in category 1

  • odds2: Odds in category 2

  • odds_ratio: Ratio of odds

  • log_odds_ratio: Log of odds ratio (positive = more in compared category)

  • variance: Variance of the log ratio, 1/(count1 + 1) + 1/(count2 + 1)

  • z_score: Log ratio divided by its standard error

Terms are ranked by absolute z-score.

Examples

# \donttest{
articles <- TextAnalysisR::SpecialEduTech[1:20, ]
corpus <- quanteda::corpus(
  articles$abstract,
  docvars = data.frame(reference_type = articles$reference_type)
)
dfm_object <- quanteda::dfm(quanteda::tokens(corpus))
log_odds <- calculate_log_odds_ratio(dfm_object, "reference_type")
# }