This report was automatically generated with the R package knitr (version 1.5).

library(faraway)
data(gala, package = "faraway")
lmod <- lm(Species ~ Area + Elevation + Nearest + Scruz + Adjacent, gala)
sumary(lmod)
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  7.06822   19.15420    0.37   0.7154
Area        -0.02394    0.02242   -1.07   0.2963
Elevation    0.31946    0.05366    5.95  3.8e-06
Nearest      0.00914    1.05414    0.01   0.9932
Scruz       -0.24052    0.21540   -1.12   0.2752
Adjacent    -0.07480    0.01770   -4.23   0.0003

n = 30, p = 6, Residual SE = 60.98, R-Squared = 0.77
sumary(lm(Species ~ Elevation, gala))
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  11.3351    19.2053    0.59     0.56
Elevation     0.2008     0.0346    5.80  3.2e-06

n = 30, p = 2, Residual SE = 78.66, R-Squared = 0.55
plot(Species ~ Elevation, gala)
abline(11.3, 0.201)
colMeans(gala)
  Species  Endemics      Area Elevation   Nearest     Scruz  Adjacent 
    85.23     26.10    261.71    368.03     10.06     56.98    261.10 
p <- predict(lmod, data.frame(Area = 261.7, Elevation = gala$Elevation, Nearest = 10.06, 
    Scruz = 56.98, Adjacent = 261.1))
i <- order(gala$Elevation)
lines(gala$Elevation[i], p[i], lty = 2)

plot of chunk unnamed-chunk-1

data(newhamp, package = "faraway")
colSums(newhamp[newhamp$votesys == "D", 2:3])
  Obama Clinton 
  86353   96890 
colSums(newhamp[newhamp$votesys == "H", 2:3])
  Obama Clinton 
  16926   14471 
newhamp$trt <- ifelse(newhamp$votesys == "H", 1, 0)
lmodu <- lm(pObama ~ trt, newhamp)
sumary(lmodu)
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.35252    0.00517   68.15  < 2e-16
trt          0.04249    0.00851    4.99  1.1e-06

n = 276, p = 2, Residual SE = 0.07, R-Squared = 0.08
lmodz <- lm(pObama ~ trt + Dean, newhamp)
sumary(lmodz)
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.22112    0.01125   19.65   <2e-16
trt         -0.00475    0.00776   -0.61     0.54
Dean         0.52290    0.04165   12.55   <2e-16

n = 276, p = 3, Residual SE = 0.05, R-Squared = 0.42
sumary(lm(Dean ~ trt, newhamp))
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.25129    0.00599   41.99   <2e-16
trt          0.09034    0.00985    9.18   <2e-16

n = 276, p = 2, Residual SE = 0.08, R-Squared = 0.24
require(Matching)
Loading required package: Matching
Loading required package: MASS
## 
##  Matching (Version 4.8-3.4, Build Date: 2013/10/28)
##  See http://sekhon.berkeley.edu/matching for additional documentation.
##  Please cite software as:
##   Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching
##   Software with Automated Balance Optimization: The Matching package for R.''
##   Journal of Statistical Software, 42(7): 1-52. 
##
set.seed(123)
mm <- GenMatch(newhamp$trt, newhamp$Dean, ties = FALSE, caliper = 0.05, pop.size = 1000)
Loading required package: rgenoud
Loading required package: parallel
##  rgenoud (Version 5.7-12, Build Date: 2013-06-28)
##  See http://sekhon.berkeley.edu/rgenoud for additional documentation.
##  Please cite software as:
##   Walter Mebane, Jr. and Jasjeet S. Sekhon. 2011.
##   ``Genetic Optimization Using Derivatives: The rgenoud package for R.''
##   Journal of Statistical Software, 42(11): 1-26. 
##


Mon Jun 16 14:01:25 2014
Domains:
 0.000000e+00   <=  X1   <=    1.000000e+03 

Data Type: Floating Point
Operators (code number, name, population) 
    (1) Cloning...........................  122
    (2) Uniform Mutation..................  125
    (3) Boundary Mutation.................  125
    (4) Non-Uniform Mutation..............  125
    (5) Polytope Crossover................  125
    (6) Simple Crossover..................  126
    (7) Whole Non-Uniform Mutation........  125
    (8) Heuristic Crossover...............  126
    (9) Local-Minimum Crossover...........  0

SOFT Maximum Number of Generations: 100
Maximum Nonchanging Generations: 4
Population size       : 1000
Convergence Tolerance: 1.000000e-03

Not Using the BFGS Derivative Based Optimizer on the Best Individual Each Generation.
Not Checking Gradients before Stopping.
Using Out of Bounds Individuals.

Maximization Problem.
GENERATION: 0 (initializing the population)
Lexical Fit..... 2.056421e-01  9.987660e-01  
#unique......... 1000, #Total UniqueCount: 1000
var 1:
best............ 1.000000e+00
mean............ 5.085426e+02
variance........ 8.178870e+04

GENERATION: 1
Lexical Fit..... 3.732776e-01  9.987660e-01  
#unique......... 600, #Total UniqueCount: 1600
var 1:
best............ 4.466534e-03
mean............ 3.105404e+02
variance........ 8.628378e+04

GENERATION: 2
Lexical Fit..... 9.987660e-01  9.993474e-01  
#unique......... 602, #Total UniqueCount: 2202
var 1:
best............ 1.603673e-03
mean............ 9.326741e+01
variance........ 4.261583e+04

GENERATION: 3
Lexical Fit..... 9.987660e-01  9.993474e-01  
#unique......... 622, #Total UniqueCount: 2824
var 1:
best............ 1.603673e-03
mean............ 7.865585e+01
variance........ 3.542311e+04

GENERATION: 4
Lexical Fit..... 9.987660e-01  9.993474e-01  
#unique......... 431, #Total UniqueCount: 3255
var 1:
best............ 1.603673e-03
mean............ 7.472079e+01
variance........ 3.081586e+04

GENERATION: 5
Lexical Fit..... 9.987660e-01  9.993474e-01  
#unique......... 435, #Total UniqueCount: 3690
var 1:
best............ 1.603673e-03
mean............ 7.505392e+01
variance........ 3.198554e+04

GENERATION: 6
Lexical Fit..... 9.987660e-01  9.993474e-01  
#unique......... 430, #Total UniqueCount: 4120
var 1:
best............ 1.603673e-03
mean............ 6.608551e+01
variance........ 2.743237e+04

GENERATION: 7
Lexical Fit..... 9.987660e-01  9.993474e-01  
#unique......... 415, #Total UniqueCount: 4535
var 1:
best............ 1.603673e-03
mean............ 7.352388e+01
variance........ 3.293366e+04

'wait.generations' limit reached.
No significant improvement in 4 generations.

Solution Lexical Fitness Value:
9.987660e-01  9.993474e-01  

Parameters at the Solution:

 X[ 1] :    1.603673e-03

Solution Found Generation 2
Number of Generations Run 7

Mon Jun 16 14:01:34 2014
Total run time : 0 hours 0 minutes and 9 seconds
head(mm$matches[, 1:2])
     [,1] [,2]
[1,]    4  168
[2,]   17  169
[3,]   18   53
[4,]   19   83
[5,]   21  246
[6,]   22   95
newhamp[c(4, 218), c("Dean", "pObama", "trt")]
               Dean pObama trt
CenterHarbor 0.2849 0.3433   1
Northwood    0.2826 0.3369   0
plot(pObama ~ Dean, newhamp, pch = trt + 1)
with(newhamp, segments(Dean[mm$match[, 1]], pObama[mm$match[, 1]], Dean[mm$match[, 
    2]], pObama[mm$match[, 2]]))

plot of chunk unnamed-chunk-1

pdiff <- newhamp$pObama[mm$matches[, 1]] - newhamp$pObama[mm$matches[, 2]]
t.test(pdiff)

    One Sample t-test

data:  pdiff
t = -1.693, df = 86, p-value = 0.09413
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 -0.033341  0.002674
sample estimates:
mean of x 
 -0.01533 
plot(pdiff ~ newhamp$Dean[mm$matches[, 1]], xlab = "Dean", ylab = "Hand-Digital")
abline(h = 0)

plot of chunk unnamed-chunk-1

plot(pObama ~ Dean, newhamp, pch = trt + 1)
abline(h = c(0.353, 0.353 + 0.042), lty = 1:2)
abline(0.221, 0.5229)
abline(0.221 - 0.005, 0.5229, lty = 2)
with(newhamp, segments(Dean[mm$match[, 1]], pObama[mm$match[, 1]], Dean[mm$match[, 
    2]], pObama[mm$match[, 2]], col = gray(0.75)))

plot of chunk unnamed-chunk-1

The R session information (including the OS info, R version and all packages used):

sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-apple-darwin13.1.0 (64-bit)

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

attached base packages:
[1] parallel  graphics  grDevices utils     datasets  methods   stats    
[8] base     

other attached packages:
[1] rgenoud_5.7-12   Matching_4.8-3.4 MASS_7.3-31      faraway_1.0.6   
[5] knitr_1.5        ggplot2_0.9.3.1 

loaded via a namespace (and not attached):
 [1] colorspace_1.2-4   dichromat_2.0-0    digest_0.6.4      
 [4] evaluate_0.5.3     formatR_0.10       grid_3.1.0        
 [7] gtable_0.1.2       labeling_0.2       munsell_0.4.2     
[10] plyr_1.8.1         proto_0.3-10       RColorBrewer_1.0-5
[13] Rcpp_0.11.1        reshape2_1.2.2     scales_0.2.3      
[16] stringr_0.6.2      tools_3.1.0       
Sys.time()
[1] "2014-06-16 14:01:34 BST"