require(mosaic)

## Loading required package: mosaic

## Loading required package: lattice

## Loading required package: grid

## Loading required package: survival

## Loading required package: splines

## Loading required package: Hmisc

## Hmisc library by Frank E Harrell Jr
## 
## Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview') to see overall
## documentation.
## 
## NOTE:Hmisc no longer redefines [.factor to drop unused levels when
## subsetting.  To get the old behavior of Hmisc type dropUnusedLevels().

## Attaching package: 'Hmisc'

## The following object(s) are masked from 'package:survival':
## 
## untangle.specials

## The following object(s) are masked from 'package:base':
## 
## format.pval, round.POSIXt, trunc.POSIXt, units

## Attaching package: 'mosaic'

## The following object(s) are masked from 'package:Hmisc':
## 
## do

## The following object(s) are masked from 'package:stats':
## 
## binom.test, D, median, prop.test, sd, var

## The following object(s) are masked from 'package:base':
## 
## max, mean, min, print, sample

file1 = "Group-A Unemployment Updated.csv"
emp = read.csv(file1)
emp10 = subset(emp, Year == 2011)
emp11 = subset(emp, Year == 2010)
y = ifelse(emp11$Empstat == "employed", 1, 0)
mod1b = glm(y ~ Age + Educ, data = emp11, family = "binomial")
summary(mod1b)

## 
## Call:
## glm(formula = y ~ Age + Educ, family = "binomial", data = emp11)
## 
## Deviance Residuals: 
##    Min      1Q  Median      3Q     Max  
## -3.228   0.237   0.312   0.402   0.771  
## 
## Coefficients:
##               Estimate Std. Error z value Pr(>|z|)    
## (Intercept)    1.85483    0.06417   28.91  < 2e-16 ***
## Age            0.03094    0.00106   29.14  < 2e-16 ***
## Educba         0.26593    0.06302    4.22  2.4e-05 ***
## Educcollege   -0.24001    0.05861   -4.09  4.2e-05 ***
## Educdoctorate  1.33303    0.26439    5.04  4.6e-07 ***
## Educhsgrad    -0.64698    0.05419  -11.94  < 2e-16 ***
## Educjrhigh    -0.94833    0.10275   -9.23  < 2e-16 ***
## Educma         0.67828    0.09522    7.12  1.1e-12 ***
## Educnone      -1.28831    0.22306   -5.78  7.7e-09 ***
## Educprimary   -0.96123    0.09265  -10.37  < 2e-16 ***
## Educprof       0.87394    0.20788    4.20  2.6e-05 ***
## Educsomehs    -1.05591    0.05994  -17.62  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 46602  on 98757  degrees of freedom
## Residual deviance: 43781  on 98746  degrees of freedom
## AIC: 43805
## 
## Number of Fisher Scoring iterations: 7

anova(mod1b, test = "Chisq")

## Analysis of Deviance Table
## 
## Model: binomial, link: logit
## 
## Response: y
## 
## Terms added sequentially (first to last)
## 
## 
##      Df Deviance Resid. Df Resid. Dev Pr(>Chi)    
## NULL                 98757      46602             
## Age   1     1456     98756      45146   <2e-16 ***
## Educ 10     1365     98746      43781   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

plotPoints(jitter(y) ~ Age, data = emp11, col = "gray")
fit.empstat = makeFun(mod1b)
plotFun(fit.empstat(Age = x, Educ = "none") ~ x, add = TRUE, col = "dark red")
plotFun(fit.empstat(Age = x, Educ = "primary") ~ x, add = TRUE, col = "red")
plotFun(fit.empstat(Age = x, Educ = "jrhigh") ~ x, add = TRUE, col = "orange")
plotFun(fit.empstat(Age = x, Educ = "somehs") ~ x, add = TRUE, col = "gold")
plotFun(fit.empstat(Age = x, Educ = "hsgrad") ~ x, add = TRUE, col = "yellow")
plotFun(fit.empstat(Age = x, Educ = "college") ~ x, add = TRUE, col = "light green")
plotFun(fit.empstat(Age = x, Educ = "prof") ~ x, add = TRUE, col = "dark green")
plotFun(fit.empstat(Age = x, Educ = "assoc") ~ x, add = TRUE, col = "light blue")
plotFun(fit.empstat(Age = x, Educ = "ba") ~ x, add = TRUE, col = "dark blue")
plotFun(fit.empstat(Age = x, Educ = "ma") ~ x, add = TRUE, col = "purple")
plotFun(fit.empstat(Age = x, Educ = "doctorate") ~ x, add = TRUE, col = "magenta")