Newitcv output

R/helper_output_print.R

@@ -8,68 +8,60 @@ output_print <- function(est_eff, beta_threshhold, bias = NULL, sustain = NULL,
       cat("\n")
       cat(paste0("RIR = ", round(recase, 3), "\n"))
       cat("\n")
-      cat(paste0("You entered an estimated effect of ", round(est_eff, 3), ". To invalidate"))
+      cat(paste0("The estimated effect is ", round(est_eff, 3), ". To invalidate the inference of an effect using"))
       cat("\n")
-      cat(paste0("the inference of an effect using the threshold of ", round(beta_threshhold, 3), " for"))
+      cat(paste0("the threshold of ", round(beta_threshhold, 3), " for statistical significance with alpha = ", alpha, ", ", round(bias, 3), "% of"))
       cat("\n")
-      cat(paste0("statistical significance with alpha = ", alpha, ", ", round(bias, 3), "% of the"))
+      cat(paste0("the (", round(est_eff, 3), ") estimate would have to be due to bias. This implies that to invalidate"))
       cat("\n")
-      cat(paste0("(", round(est_eff, 3), ") estimate would have to be due to bias. This implies"))
+      cat(paste0("the inference one would expect to have to replace ", round(recase, 3), " (", round(bias, 3), "%) observations"))
       cat("\n")
-      cat("that to invalidate the inference one would expect to have to\n")
-      cat(paste0("replace ", round(recase, 3), " (", round(bias, 3), "%) observations with cases for which the"))
-      cat("\n")    
-      cat(paste0("treatment effect is ", nu, " (RIR = ", round(recase, 3), ").\n"))
+      cat(paste0("with cases for which the treatment effect is ", nu, " (RIR = ", round(recase, 3), ").\n"))
       cat("\n")    
     } else if ((abs(est_eff) > abs(beta_threshhold)) & is.na(eff_thr) == FALSE) {
       cat("TO INVALIDATE:\n")
       cat("\n")
       cat(paste0("RIR = ", round(recase, 3), "\n"))
       cat("\n")
-      cat(paste0("You entered an effect of ", round(est_eff, 3), ", and specified a threshold"))
-      cat("\n")
-      cat(paste0("for inference of ", round(eff_thr, 3), ". To invalidate the inference based on your"))
+      cat(paste0("The estimated effect is ", round(est_eff, 3), ", and specified threshold for inference is ", round(eff_thr, 3), "."))
       cat("\n")
-      cat(paste0("estimate, ", round(bias, 3), "% of the (", round(est_eff, 3), ") estimate would have to be due to"))
+      cat(paste0("To invalidate the inference based on your estimate, ", round(bias, 3), "% of the (", round(est_eff, 3), ")"))
       cat("\n")
-      cat(paste0("bias. This implies that to invalidate the inference one would"))
+      cat(paste0("estimate would have to be due to bias. This implies that to invalidate"))
       cat("\n")
-      cat(paste0("expect to have to replace ", round(recase, 3), " (", round(bias, 3), "%) observations with"))
+      cat(paste0("the inference one would expect to have to replace ", round(recase, 3), " (", round(bias, 3), "%) observation"))
       cat("\n")
-      cat(paste0("cases for which the treatment effect is ", nu, " (RIR = ", round(recase, 3), ").\n"))
+      cat(paste0("with cases for which the treatment effect is ", nu, " (RIR = ", round(recase, 3), ").\n"))
       cat("\n") 
     } else if ((abs(est_eff) < abs(beta_threshhold)) & is.na(eff_thr) == TRUE) {
       cat("TO SUSTAIN:\n", sep = "")
       cat("\n")
       cat(paste0("RIR = ", round(recase, 3), "\n"))
       cat("\n")
-      cat(paste0("You entered an estimated effect of ", round(est_eff, 3), ". The threshold value for"))
+      cat(paste0("The estimated effect is ", round(est_eff, 3), ". The threshold value for statistical significance"))
       cat("\n")
-      cat(paste0("statistical significance is ", round(beta_threshhold, 3), " (alpha = ", alpha, "). To reach that"))
+      cat(paste0("is ", round(beta_threshhold, 3), " (alpha = ", alpha, "). To reach that threshold, ", round(sustain, 3), "% of the (", round(est_eff, 3), ") estimate"))
       cat("\n")
-      cat(paste0("threshold, ", round(sustain, 3), "% of the (", round(est_eff, 3), ") estimate would have to be due to"))
+      cat(paste0("would have to be due to bias. This implies to sustain an inference one would"))
       cat("\n")
-      cat("bias. This implies that to sustain an inference one would expect to")
+      cat(paste0("expect to have to replace ", round(recase, 3), " (", round(sustain, 3), "%) observations with effect of ", nu, " with cases"))
       cat("\n")
-      cat(paste0("have to replace ", round(recase, 3), " (", round(sustain, 3), "%) observations with effect of ", nu, " with\n"))
-      cat(paste0("cases with effect of ", round(beta_threshhold, 3), " (RIR = ", round(recase, 3), ").\n"))
+      cat(paste0("with effect of ", round(beta_threshhold, 3), " (RIR = ", round(recase, 3), ").\n"))
       cat("\n")
     } else if ((abs(est_eff) < abs(beta_threshhold)) & is.na(eff_thr) == FALSE) {
       cat("TO SUSTAIN:\n", sep = "")
       cat("\n")
       cat(paste0("RIR = ", round(recase, 3), "\n"))
       cat("\n")
-      cat(paste0("You entered an effect size of ", round(est_eff, 3), ", and specified a threshold"))
-      cat("\n")
-      cat(paste0("for inference of ", round(eff_thr, 3), ". To reach that threshold, ", round(sustain, 3), "% of the" ))
+      cat(paste0("The estimated effect is ", round(est_eff, 3), ", and specified threshold for inference is ", round(eff_thr, 3), "."))
       cat("\n")
-      cat(paste0("(", round(est_eff, 3), ") estimate would have to be due to bias. This implies"))
+      cat(paste0("To reach that threshold, ", round(sustain, 3), "% of the (", round(est_eff, 3), ") estimate would have to be due"))
       cat("\n")
-      cat("that to sustain an inference one would expect to have to replace ")
+      cat(paste0("to bias. This implies that to sustain an inference one would expect to have"))
       cat("\n")
-      cat(paste0(round(recase, 3), " (", round(sustain, 3), "%) observations with effect of ", nu, " with cases"))
+      cat(paste0("to replace ", round(recase, 3), " (", round(sustain, 3), "%) observations with effect of ", nu, " with cases with effect"))
       cat("\n")
-      cat(paste0("with effect of ", round(beta_threshhold, 3), " (RIR = ", round(recase, 3), ").\n"))
+      cat(paste0("of ", round(beta_threshhold, 3), " (RIR = ", round(recase, 3), ").\n"))
       cat("\n")
     } else if (est_eff == beta_threshhold) {
       warning("The coefficient is exactly equal to the threshold.\n")
@@ -105,40 +97,39 @@ if (requireNamespace("htmltools", quietly = TRUE)) {
     if (abs(obs_r) > abs(critical_r) & obs_r > 0) {
       cat("The minimum impact of an omitted variable to invalidate an inference")
       cat("\n")
-      cat(paste0("for a null hypothesis of 0 effect is based on a correlation of ", r_con))
+      cat(paste0("for a null hypothesis of 0 effect is based on a correlation of ", round(r_con, 3)))
       cat("\n")
-      cat(paste0("with the outcome and at ", r_con, " with the predictor of interest (conditioning"))
+      cat(paste0("with the outcome and ", round(r_con, 3), " with the predictor of interest (conditioning"))
       cat("\n")
-      cat(paste0("on all observed covariates in the model) based on a threshold of ", round(critical_r, 3)))
+      cat("on all observed covariates in the model; signs are interchangeable)")
       cat("\n")
-      cat("for statistical significance (alpha = ", alpha, ").\n",
-          sep = "")
+      cat(paste0("based on a threshold of ", round(critical_r, 3), " for statistical significance (alpha = ", alpha, ").\n"))
       cat("\n")
       cat("Correspondingly the impact of an omitted variable (as defined in Frank 2000) must be ") 
       cat("\n")
-      cat(r_con, " X ", r_con, " = ", round(r_con^2, 3), " to invalidate an inference for a null hypothesis of 0 effect.\n", sep = "")
+      cat(round(r_con, 3), " X ", round(r_con, 3), " = ", round(r_con^2, 3), " to invalidate an inference for a null hypothesis of 0 effect.\n", sep = "")
     } else if (abs(obs_r) > abs(critical_r) & obs_r < 0) {
       cat("The minimum (in absolute value) impact of an omitted variable to")
       cat("\n")
       cat(paste0("invalidate an inference for a null hypothesis of 0 effect is based on"))
       cat("\n")
-      cat(paste0("a correlation of ", -r_con, " with the outcome and at ", r_con, " with the predictor"))
+      cat(paste0("a correlation of ", -round(r_con, 3), " with the outcome and ", round(r_con, 3), " with the predictor"))
       cat("\n")
       cat("of interest (conditioning on all observed covariates in the model;")
       cat("\n")
-      cat(paste0("signs are interchangeable) based on a threshold of ", round(beta_threshhold, 3), " for"))
+      cat(paste0("signs are interchangeable) based on a threshold of ", round(critical_r, 3), " for"))
       cat("\n")
       cat("statistical significance (alpha = ", alpha, ").\n", sep = "")
       cat("\n")
       cat("Correspondingly the impact of an omitted variable (as defined in Frank 2000) must be ") 
       cat("\n")
-      cat(-r_con, " X ", r_con, " = ", -round(r_con^2, 3), " to invalidate an inference for a null hypothesis of 0 effect.\n", sep = "")
+      cat(-round(r_con, 3), " X ", round(r_con, 3), " = ", -round(r_con^2, 3), " to invalidate an inference for a null hypothesis of 0 effect.\n", sep = "")
     } else if (abs(obs_r) < abs(critical_r) & obs_r > 0) {
       cat("The maximum impact (in absolute value) of an omitted variable to") 
       cat("\n")
       cat("sustain an inference for a null hypothesis of 0 effect is based on")
       cat("\n")
-      cat(paste0("a correlation of ", -r_con, " with the outcome an at ", r_con, " with the predictor"))
+      cat(paste0("a correlation of ", -round(r_con, 3), " with the outcome and ", round(r_con, 3), " with the predictor"))
       cat("\n")
       cat("of interest (conditioning on all observed covariates in the model;")
       cat("\n")
@@ -148,24 +139,30 @@ if (requireNamespace("htmltools", quietly = TRUE)) {
       cat("\n")
       cat("Correspondingly the impact of an omitted variable (as defined in Frank 2000) must be ")
       cat("\n")
-      cat(-r_con, " X ", r_con, " = ", -round(r_con^2, 3), " to sustain an inference for a null hypothesis of 0 effect.\n", sep = "")
+      cat(-round(r_con, 3), " X ", round(r_con, 3), " = ", -round(r_con^2, 3), " to sustain an inference for a null hypothesis of 0 effect.\n", sep = "")
     } else if (abs(obs_r) < abs(critical_r) & obs_r < 0) {
       cat("The maximum impact of an omitted variable to sustain an inference")
       cat("\n")
-      cat(paste0("for a null hypothesis of 0 effect is based on a correlation of ", r_con))
+      cat(paste0("for a null hypothesis of 0 effect is based on a correlation of ", round(r_con, 3)))
       cat("\n")
-      cat(paste0("with the outcome and at ", r_con, " with the predictor of interest (conditioning"))
+      cat(paste0("with the outcome and ", round(r_con, 3), " with the predictor of interest (conditioning"))
       cat("\n")
-      cat(paste0("on all observed covariates in the model) based on a threshold of ", round(beta_threshhold, 3)))
+      cat("on all observed covariates in the model; signs are interchageable)")
       cat("\n")
-      cat("for statistical significance (alpha = ", alpha, ").\n", sep = "")
+      cat(paste0("based on a threshold of ", round(beta_threshhold, 3), " for statistical significance (alpha = ", alpha, ").\n"))
       cat("\n")
       cat("Correspondingly the impact of an omitted variable (as defined in Frank 2000) must be ")
       cat("\n")
-      cat(r_con, " X ", r_con, " = ", round(r_con^2, 3), " to sustain an inference for a null hypothesis of 0 effect.\n", sep = "")
+      cat(round(r_con, 3), " X ", round(r_con, 3), " = ", round(r_con^2, 3), " to sustain an inference for a null hypothesis of 0 effect.\n", sep = "")
     } else if (obs_r == critical_r) {
       warning("The correlation is exactly equal to the threshold.\n")
     }
+    cat("\n")
+    cat("For calculation of unconditional ITCV, request raw output. When using pkonfound(),")
+    cat("\n")
+    cat("additionally include the R2, sdx, and sdy as input.")
+    cat("\n")   
+    cat("\n")   
     cat("See Frank (2000) for a description of the method.")
     cat("\n")
     cat("\n")

R/konfound-lm.R

@@ -19,7 +19,7 @@ konfound_lm <- function(model_object, tested_variable_string, test_all, alpha, t
   sdy <- unname(sqrt(diag(var(model_object$model)))[1])
   R2 <- summary(model_object)$r.squared
 
-  if (test_all == FALSE) {
+  if (test_all == FALSE | n_covariates == 1) {
     out <- test_sensitivity(
       est_eff = est_eff,
       std_err = std_err,
@@ -40,7 +40,10 @@ konfound_lm <- function(model_object, tested_variable_string, test_all, alpha, t
     )
     return(out)
   } else {
-    message("Note that this output is calculated based on the correlation-based approach used in mkonfound()")
+    message("The mkonfound command is used which evaluates RIR in terms of a correlation-based approach
+    to support comparison among the robustness of the inferences across the covariates. 
+    ITCV is for conditional correlations. To generate unconditional ITCV, use the pkonfound 
+    command for each predictor separately.")
     d <- data.frame(t = est_eff / std_err, df = (n_obs - n_covariates - 1))
     o <- mkonfound(d, .data$t, .data$df)
     term_names <- dplyr::select(tidy_output, var_name = .data$term) # remove the first row for intercept

R/konfound.R

@@ -81,7 +81,7 @@ konfound <- function(model_object,
   }
 
   if (inherits(model_object, "glm") & two_by_two == FALSE) {
-    message("Note that for a non-linear model, impact threshold should not be interpreted.")
+    message("Note that if your model is a logistic regression, we recommend using the pkonfound command for logistic regression with manually entered parameter estimates and other quantities.")
     message("Note that this is only an approximation. For exact results in terms of the number of cases that must be switched from treatment success to treatment failure to invalidate the inference see: https://msu.edu/~kenfrank/non%20linear%20replacement%20treatment.xlsm")
     message("If a dichotomous independent variable is used, consider using the 2X2 table approach enabled with the argument two_by_two = TRUE")
     output <- konfound_glm(

R/nonlinear_auxiliary.R

@@ -129,7 +129,8 @@ getswitch <- function(table_bstart, thr_t, switch_trm, n_obs) {
     b_tryall <- b - (b - 1) * (1 - as.numeric(switch_trm))
     tryall_t <- get_t_kfnl(a_tryall, b_tryall, c_tryall, d_tryall)
     tryall_est <- log(a_tryall*d_tryall/c_tryall/b_tryall)
-    allnotenough <- isTRUE(thr_t - tryall_t > 0 & tryall_est*est_eff_start > 0)
+    allnotenough <- isTRUE(thr_t - tryall_t > 0 & 
+                               tryall_est * est_eff_start >= 0)
   }
   if (t_start > thr_t) {
     # transfer cases from A to B or D to C to decrease odds ratio
@@ -139,7 +140,7 @@ getswitch <- function(table_bstart, thr_t, switch_trm, n_obs) {
     b_tryall <- b + (a - 1) * (1 - as.numeric(switch_trm))
     tryall_t <- get_t_kfnl(a_tryall, b_tryall, c_tryall, d_tryall)
     tryall_est <- log(a_tryall*d_tryall/c_tryall/b_tryall)
-    allnotenough <- isTRUE(tryall_t - thr_t > 0 & tryall_est*est_eff_start > 0)
+    allnotenough <- isTRUE(tryall_t - thr_t > 0 & tryall_est*est_eff_start >= 0)
   }
 
   ### run following if transfering one row is enough
@@ -388,7 +389,7 @@ if (!dcroddsratio_start) {
   b_tryall <- b - (b - 1) * (1 - as.numeric(switch_trm))
   tryall_p <- chisq_p(a_tryall, b_tryall, c_tryall, d_tryall)
   tryall_est <- log(a_tryall*d_tryall/c_tryall/b_tryall)
-  allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est< 0 & tryall_est*est > 0)
+  allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est< 0 & tryall_est*est >= 0)
 }
 if (dcroddsratio_start ) {
   # transfer cases from A to B or D to C to decrease odds ratio
@@ -398,7 +399,7 @@ if (dcroddsratio_start ) {
   b_tryall <- b + (a - 1) * (1 - as.numeric(switch_trm))
   tryall_p <- chisq_p(a_tryall, b_tryall, c_tryall, d_tryall)
   tryall_est <- log(a_tryall*d_tryall/c_tryall/b_tryall)
-  allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est> 0  & tryall_est*est > 0)
+  allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est> 0  & tryall_est*est >= 0)
 }
 
 ### run following if transfering one row is enough
@@ -732,7 +733,7 @@ getswitch_fisher <- function(a, b, c, d, thr_p = 0.05, switch_trm = T){
     if (d_tryall == 0) {d_tryall <- d_tryall + 0.5}
     tryall_p <- fisher_p(a_tryall, b_tryall, c_tryall, d_tryall)
     tryall_est <- log(a_tryall*d_tryall/c_tryall/b_tryall)
-    allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est< 0 & tryall_est*est > 0)
+    allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est< 0 & tryall_est*est >= 0)
   }
   if (dcroddsratio_start ) {
     # transfer cases from A to B or D to C to decrease odds ratio
@@ -746,7 +747,7 @@ getswitch_fisher <- function(a, b, c, d, thr_p = 0.05, switch_trm = T){
     if (d_tryall == 0) {d_tryall <- d_tryall + 0.5}
     tryall_p <- fisher_p(a_tryall, b_tryall, c_tryall, d_tryall)
     tryall_est <- log(a_tryall*d_tryall/c_tryall/b_tryall)
-    allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est> 0  & tryall_est*est > 0)
+    allnotenough <- isTRUE((thr_p-tryall_p)*tryall_est> 0  & tryall_est*est >= 0)
   }
 
   ### run following if transfering one row is enough

R/test_sensitivity.R

@@ -163,7 +163,7 @@ if (signsuppression == 1) warning("signsuppression is defined by a threshold of
   itcv <- signITCV * abs(act_r - critical_r) / (1 + mp * abs(critical_r))
 
   # finding correlation of confound to invalidate / sustain inference
-  r_con <- round(sqrt(abs(itcv)), 3)
+  r_con <- sqrt(abs(itcv))
 
   ## calculate the unconditional ITCV if user inputs sdx, sdy and R2
   if (!is.na(sdx) & !is.na(sdy) & !is.na(R2) & (n_covariates > 0)) {