COPD incidence recalibrated

DESCRIPTION

@@ -1,22 +1,22 @@
 Package: epicR
 Title: R Package for Evaluation Platform in COPD
-Version: 0.28.2.999
+Version: 0.29.0
 Authors@R: c(
     person("Mohsen", "Sadatsafavi", email = "[email protected]", role = c("aut", "cph")),
     person("Amin", "Adibi", email = "[email protected]", role = c("aut", "cre")),
     person("Kate", "Johnson", email = "[email protected]", role = c("aut")))
 Description: Evaluation Platform in COPD (EPIC) is a Discrete Event Simulation (DES) model that simulates health outcomes of COPD patients based on demographics and individual-level risk factors, based on the model published in Sadatsafavi et al. (2019) <doi:10.1177/0272989X18824098>.
 Depends:
-    R (>= 3.6.0)
+    R (>= 4.1.0)
 License: GPL-3
 Encoding: UTF-8
 LazyData: true
 Imports:
-    Rcpp (>= 1.0.6),
-    RcppArmadillo (>= 0.10.1),
+    Rcpp (>= 1.0.8),
+    RcppArmadillo (>= 0.11.2),
     graphics,
     stats,
-    ggplot2 (>= 3.1.0),
+    ggplot2 (>= 3.3.6),
     ggthemes,
     sqldf,
     jsonlite,

R/calibration.R

@@ -189,7 +189,7 @@ calibrate_smoking <- function() {
 #' @return regression co-efficients as files
 #' @export
 
-calibrate_COPD_inc<-function(nIterations=500,
+calibrate_COPD_inc<-function(nIterations=100,
                            nPatients=100000,
                            time_horizon=20)
 {
@@ -291,8 +291,8 @@ calibrate_COPD_inc<-function(nIterations=500,
   plot(ggplot2::qplot(iteration, resid_intercept_men, data=iteration_resid, size=I(1),  main = "Residue for logit intercept - Men"))
   plot(ggplot2::qplot(iteration, resid_intercept_women, data=iteration_resid, size=I(1),  main = "Residue for logit intercept - Women"))
 
-  res_male<-glm(data=dataF[which(dataF[,'sex']==0),],formula=copd~age+pack_years+year,family=binomial(link=logit))
-  res_female<-glm(data=dataF[which(dataF[,'sex']==1),],formula=copd~age+pack_years+year,family=binomial(link=logit))
+  res_male<-glm(data=dataF[which(dataF[,'female']==0),],formula=copd~age+pack_years+year,family=binomial(link=logit))
+  res_female<-glm(data=dataF[which(dataF[,'female']==1),],formula=copd~age+pack_years+year,family=binomial(link=logit))
 
   message(coefficients(res_male))
   message(coefficients(res_female))

R/input.R

@@ -216,11 +216,11 @@ init_input <- function() {
 
 
   input_help$COPD$ln_h_COPD_betas_by_sex <- "Log-hazard of developing COPD (FEV1/FVC<LLN) for those who did not have COPD at creation time (separately by sex)"
-  input$COPD$ln_h_COPD_betas_by_sex <- cbind(male = c(Intercept = -7.86555434, age = 0.03261784, age2 = 0, pack_years =  0.03076498,
+  input$COPD$ln_h_COPD_betas_by_sex <- cbind(male = c(Intercept =  -7.97107937, age = 0.03245063, age2 = 0, pack_years =  0.03578899,
                                                       smoking_status = 0, year = 0, asthma = 0),
-                                             female = c(Intercept = -7.75884176, age = 0.02793072, age2 = 0, pack_years = 0.04184035,
+                                             female = c(Intercept = -7.78520064, age = 0.02975571, age2 = 0, pack_years = 0.04087865,
                                                         smoking_status =  0, year = 0, asthma = 0))
-  input_ref$COPD$ln_h_COPD_betas_by_sex <- "Amin's Iterative solution. Last Updated on 2018-02-10 (0.18.0)"
+  input_ref$COPD$ln_h_COPD_betas_by_sex <- "Amin's Iterative solution. Last Updated on 2022-06-33 (0.29.0)"
 
 
   ## Lung function