added flu_stats_fisher_only.R containing separate dfs based on var factor levels

2020-11-19 18:05:57 +00:00 · 2020-11-19 18:05:57 +00:00 · a6cbaab40a
commit a6cbaab40a
parent 74769b9a38
1 changed files with 181 additions and 0 deletions
--- a/flu_stats_fisher_only.R
+++ b/flu_stats_fisher_only.R
@ -0,0 +1,181 @@
+#!/usr/bin/Rscript   
+getwd()
+setwd("~/git/mosaic_2020/")
+getwd()
+############################################################
+# TASK: Contingency table analysis i.e chisq and fishers
+# data: clincial data of flu positive adult patients
+# group: obesity
+
+# Chisq test
+#https://www.google.com/search?q=chisq+test+on+long+format+data+in+R+using+group+by&source=lmns&bih=828&biw=1280&client=firefox-b-d&hl=en-GB&sa=X&ved=2ahUKEwjItpL7xI7tAhUGTBoKHXlSBa8Q_AUoAHoECAEQAA
+############################################################
+
+#=============
+# Input
+#=============
+source("data_extraction_formatting_clinical.R")
+str(clinical_df_ics)
+
+clinical_df_ics$sfluv = as.integer(clinical_df_ics$sfluv)
+clinical_df_ics$h1n1v  = as.integer(clinical_df_ics$h1n1v)
+
+#=============
+# Output
+#=============
+
+########################################################################
+# Fisher's test for clinical data b/w obesity groups
+########################################################################
+categorical_cols = c( "death"
+                      #, "obesity"
+                      #, "flustat"
+                      , "sfluv"
+                      , "h1n1v"
+                      , "gender"
+                      , "asthma"
+                      #, "o2_sat_suppl" ---> not recoded!?
+                      , "ethnicity"
+                      , "smoking"
+                      , "ia_cxr"
+                      , "max_resp_score"
+                      , "T1_resp_score"
+                      , "com_noasthma"
+                      , "T2_resp_score"
+                      , "inresp_sev"
+                      , "steroid"
+                      , "age_bins"
+                      , "o2_sat_bin"
+                      , "onset_initial_bin"
+                      , "t1_resp_recoded"
+                      , "steroid_ics")
+
+metadata_cols = c("mosaic", "obesity")
+
+categ_df = clinical_df_ics[, c(metadata_cols, categorical_cols)]
+
+my_categ_cols = colnames(categ_df)[!colnames(categ_df)%in%metadata_cols]
+
+if ( length(my_categ_cols) == ncol(categ_df) - length(metadata_cols) ){
+  cat("PASS: variables for chisq test successfully extracted")
+}else{
+  cat("FAIL: length mismatch when extracting variables for chisq")
+  quit()
+}
+
+#========================================================
+# Data: for fisher:
+#2 levels: with OR
+#3 levels: without OR
+#========================================================
+stats_df = subset(categ_df, select = -c(mosaic))
+
+stats_df_copy = stats_df
+int_vars <- lapply(stats_df_copy, class)%in%c("integer", "numeric")
+int_vars
+stats_df_copy[, int_vars] <- lapply(stats_df_copy[, int_vars], as.factor)
+str(stats_df_copy)
+
+#-----------
+# 2 levels
+#-----------
+two_lev = lapply(stats_df_copy, nlevels) == 2
+fisher_cols_df1  = names(two_lev)[two_lev == TRUE]
+fisher_cols_df1
+
+cat("\nTotal no. of cols:", ncol(stats_df_copy)
+    , "\nNo. of vars with 2 factor levels:", length(fisher_cols_df1)
+    , "\nThese are:\n"
+    , fisher_cols_df1)
+
+fisher_cols_df1 = fisher_cols_df1[!fisher_cols_df1%in%metadata_cols]
+fisher_cols_df1
+
+fisher_df1 = data.frame()
+
+for (i in fisher_cols_df1){
+  cat(i, "\n===============\n")
+  df = data.frame(clinical_categ_params = NA, n_obs = NA, method = NA, test_statistic = NA, p = NA, ci_low = NA, ci_high = NA)
+  my_param_val = (get(i, stats_df))
+  tab = table(stats_df$obesity, my_param_val)
+  print(tab)
+  my_fisher_test = fisher.test(tab)
+  print(my_fisher_test)
+  
+  # extracting results
+  my_param_name = i
+  my_n_obs = sum(tab)
+  my_method = my_fisher_test$method
+  my_test_statistic = my_fisher_test$estimate[[1]] # FIXME|
+  my_pval = my_fisher_test$p.value
+  my_ci_low = my_fisher_test$conf.int[[1]]
+  my_ci_hi = my_fisher_test$conf.int[[2]]
+  
+  # assiging to loop df
+  df$clinical_categ_params = my_param_name
+  df$n_obs = my_n_obs
+  df$method = my_method 
+  df$test_statistic = my_test_statistic
+  df$p = my_pval
+  df$ci_low = my_ci_low
+  df$ci_high = my_ci_hi
+  
+  print(df)
+  fisher_df1 = rbind(fisher_df1, df) # FIXME, test_statistic col not getting created
+}
+
+#-----------
+# >2 levels
+#-----------
+multi_lev = lapply(stats_df_copy, nlevels) > 2
+fisher_cols_df2  = names(multi_lev)[multi_lev == TRUE]
+fisher_cols_df2
+
+cat("\nTotal no. of cols:", ncol(stats_df_copy)
+    , "\nNo. of vars with >2 factor levels:", length(fisher_cols_df2)
+    , "\nThese are:\n"
+    , fisher_cols_df2)
+
+
+fisher_cols_df2 = fisher_cols_df2[!fisher_cols_df2%in%metadata_cols]
+fisher_cols_df2
+
+fisher_df2 = data.frame()
+
+for (i in fisher_cols_df2){
+  cat(i, "\n===============\n")
+  df = data.frame(clinical_categ_params = NA, n_obs = NA, method = NA, test_statistic = NA , p = NA)
+  my_param_val = (get(i, stats_df))
+  tab = table(stats_df$obesity, my_param_val)
+  print(tab)
+  my_fisher_test = fisher.test(tab)
+  print(my_fisher_test)
+  
+  # extracting results
+  my_param_name = i
+  my_n_obs = sum(tab)
+  my_method = my_fisher_test$method
+  my_test_statistic = "NA i.e >2 categories"
+  my_pval = my_fisher_test$p.value
+  
+  # assiging to loop df
+  df$clinical_categ_params = my_param_name
+  df$n_obs = my_n_obs
+  df$method = my_method 
+  df$test_statistic = my_test_statistic
+  df$p = my_pval
+  
+  print(df)
+  fisher_df2 = rbind(fisher_df2, df)
+}
+#=======================================================================
+# quick tests
+tab2 = table(stats_df$obesity, stats_df$smoking)
+tab2
+test2 = fisher_test(tab2); test2 # rstatix, gives n but no other estimates
+test3 = fisher.test(stats_df$obesity, stats_df$com_noasthma); test3
+
+########################################################################
+#******************
+# write output file
+#******************