civil_comments/01_dv_example.R

   1 source('load_perspective_data.R')
   2 source("../simulations/measerr_methods.R")
   3 source("../simulations/RemembR/R/RemembeR.R")
   4
   5 change.remember.file("dv_perspective_example.RDS")
   6
   7 # for reproducibility
   8 set.seed(1111)
   9
  10 ## another simple enough example: is P(toxic | funny and white) > P(toxic | funny nand white)? Or, are funny comments more toxic when people disclose that they are white?
  11
  12 compare_dv_models <-function(pred_formula, outcome_formula, proxy_formula, df, sample.prop, remember_prefix){
  13     pred_model <- glm(pred_formula, df, family=binomial(link='logit'))
  14
  15     remember(coef(pred_model), paste0(remember_prefix, "coef_pred_model"))
  16     remember(diag(vcov((pred_model))), paste0(remember_prefix, "se_pred_model"))
  17
  18     coder_model <- glm(outcome_formula, df, family=binomial(link='logit'))
  19     remember(coef(coder_model), paste0(remember_prefix, "coef_coder_model"))
  20     remember(diag(vcov((coder_model))), paste0(remember_prefix, "se_coder_model"))
  21
  22     df_measerr_method <- copy(df)[sample(1:.N, sample.prop * .N), toxicity_coded_1 := toxicity_coded]
  23     df_measerr_method <- df_measerr_method[,toxicity_coded := toxicity_coded_1]
  24     sample_model <- glm(outcome_formula, df_measerr_method, family=binomial(link='logit'))
  25     remember(coef(sample_model), paste0(remember_prefix, "coef_sample_model"))
  26     remember(diag(vcov((sample_model))), paste0(remember_prefix, "se_sample_model"))
  27
  28     measerr_model <- measerr_mle_dv(df_measerr_method, outcome_formula, outcome_family=binomial(link='logit'), proxy_formula=proxy_formula, proxy_family=binomial(link='logit'))
  29
  30     inv_hessian = solve(measerr_model$hessian)
  31     stderr = diag(inv_hessian)
  32     remember(stderr, paste0(remember_prefix, "measerr_model_stderr"))
  33     remember(measerr_model$par, paste0(remember_prefix, "measerr_model_par"))
  34 }
  35
  36 print("running first example")
  37
  38 compare_dv_models(pred_formula = toxicity_pred ~ funny*white,
  39                   outcome_formula = toxicity_coded ~ funny*white,
  40                   proxy_formula = toxicity_pred ~ toxicity_coded*funny*white,
  41                   df=df,
  42                   sample.prop=0.01,
  43                   remember_prefix='cc_ex_tox.funny.white')
  44
  45
  46 print("running second example")
  47
  48 compare_dv_models(pred_formula = toxicity_pred ~ likes+race_disclosed,
  49                   outcome_formula = toxicity_coded ~ likes + race_disclosed,KKJ
  50                   proxy_formula = toxicity_pred ~ toxicity_coded*likes*race_disclosed,
  51                   df=df,
  52                   sample.prop=0.01,
  53                   remember_prefix='cc_ex_tox.funny.race_disclosed')
  54