Publications by Jacob M. Souch*
Problem Set 6
Table of contents A. Models i. Not controlling for age. ii. Controlling for age linearly. iii. Controlling for age and age-squared. iv. Controlling for 5-year age groups (top-coded at 85+) v. Any other(s) you may want to try, if any at all. B. Assumptions of Baseline Hazard C. Model Fit Comparison D. Logistic and Complementary Log-Log Models D...
4218 sym Python (21796 sym/29 pcs) 5 img
Problem Set 6
Table of contents A. Models i. Not controlling for age. ii. Controlling for age linearly. iii. Controlling for age and age-squared. iv. Controlling for 5-year age groups (top-coded at 85+) v. Any other(s) you may want to try, if any at all. B. Assumptions of Baseline Hazard C. Model Fit Comparison D. Logistic and Complementary Log-Log Models D...
7518 sym Python (28630 sym/37 pcs) 6 img 1 tbl
Problem Set 5
Jacob M. Souch library(readr) Warning: package 'readr' was built under R version 4.3.2 getwd() [1] "C:/Users/jacob/University of Texas at San Antonio/TEAM - Cossman Crew - General" setwd("C:/Users/jacob/Downloads") mhas0121dummies<-read.csv("MHAS0121 NO LABELS NO NEGATIVE TIMES (2).csv") mhas0121noNA<-mhas0121dummies #update.packages() #...
3739 sym Python (21711 sym/43 pcs) 3 img
Publish Document
Table of contents A. Models i. Not controlling for age. ii. Controlling for age linearly. iii. Controlling for age and age-squared. iv. Controlling for 5-year age groups (top-coded at 85+) v. Any other(s) you may want to try, if any at all. B. Assumptions of Baseline Hazard C. Model Fit Comparison D. Logistic and Complementary Log-Log Models D...
4218 sym Python (21796 sym/29 pcs) 5 img
Problem Set 5
Jacob M. Souch library(readr) Warning: package 'readr' was built under R version 4.3.2 getwd() [1] "C:/Users/jacob/University of Texas at San Antonio/TEAM - Cossman Crew - General" setwd("C:/Users/jacob/Downloads") mhas0121dummies<-read.csv("MHAS0121 NO LABELS NO NEGATIVE TIMES (2).csv") mhas0121noNA<-mhas0121dummies #update.packages() #Spli...
2461 sym Python (1024559 sym/32 pcs)
Problem Set 5
Problem Set 5 Author Jacob M. Souch Import Data library(tidyverse) Warning: package 'ggplot2' was built under R version 4.3.2 Warning: package 'readr' was built under R version 4.3.2 Warning: package 'purrr' was built under R version 4.3.2 Warning: package 'dplyr' was built under R version 4.3.2 ── Attaching core tidyverse packages �...
143 sym Python (8177 sym/28 pcs)
EHA DEM7223 Problem Set 3
Table of contents Import Data Data Preparation Models I. Multivariate parametric proportional hazards models A. Intercept-Only Exponential Model B. Female Covariate Exponential Model C. Multiple Models (Schooling) i. Exponential Model (Covariates, schooling) ii. Gompertz Model (Covariates, schooling) iii. Weibull Model (Covariates, schooling) iv....
5385 sym Python (53676 sym/177 pcs) 15 img
EHA DEM7223 Problem Set 3
Table of contents Import Data Data Preparation Models I. Multivariate parametric proportional hazards models A. Intercept-Only Exponential Model B. Female Covariate Exponential Model C. Multiple Models i. Exponential Model (Covariates) ii. Gompertz Model (Covariates) iii. Weibull Model (Covariates) iv. Log-Logistic Model (Covariates) v. Log-Norma...
4111 sym Python (39196 sym/124 pcs) 17 img
San Antonio Promise Zones
San Antonio Promise Zones Author Jacob M. Souch BLACK_tract_C <- BLACK_tract[BLACK_tract$year %in% c(2013, 2019),] %>% select(tract, year, estimate) %>% pivot_wider(names_from = year, values_from = estimate) BLACK_tract_C$Delta <- BLACK_tract_C$`2019` - BLACK_tract_C$`2013` Change <- rbind(slice_min(BLACK_tract_C, order_by = abs(Delta), n...
484 sym Python (72520 sym/140 pcs) 11 img
Blame it on the Alcohol: An Event History Analysis of Mortality Risk
Blame It on The Alcohol: An Event History Analysis of Alcohol Consumption Author Jacob M. Souch Introduction Data and Materials NHEFS: The NHEFS will be used to conduct exploratory empirical analysis. NHEFS is a national longitudinal study that was jointly initiated by the National Center for Health Statistics and the National Institute on Agi...
3908 sym Python (48788 sym/94 pcs) 11 img 4 tbl