#Step 1: Find path of data file and copy path (if using windows)
#Step 2: In the console below, type readClipboard()
#Step 3: Copy and paste path to the line below in quotes
#CHANGE BETWEEN QUOTES IN THIS LINE TO REFLECT DIRECTORY OF DATA:
myDataLocation = "/Users/jonathan/Dropbox/!EPSY 905/Lectures/11 Missing Data and MI/mv16epsy905_lecture11"
#SET WORKING DIRECTORY TO LOCATION OF DATA FILE
setwd(myDataLocation)
#IMPORT DATA AND PUT INTO DATASET
data01 = read.csv(file="mv16epsy905_lecture11.csv",header=TRUE)
#AUTOMATING PACKAGES NEEDED FOR ANALYSES--------------------------------------------------------------------
haspackage = require("mice")
## Loading required package: mice
## Loading required package: Rcpp
## mice 2.25 2015-11-09
if (haspackage==FALSE){
install.packages("mice")
}
library(mice)
haspackage = require("mvtnorm")
## Loading required package: mvtnorm
if (haspackage==FALSE){
install.packages("mvtnorm")
}
library(mvtnorm)
#centering CC at 10:---------------------------------------------------------------------------------
par(mfrow = c(1,2))
boxplot(data01$cc, main="Boxplot of College Experience (CC)")
hist(data01$cc, main = "Histogram of College Experience (CC)", xlab = "CC")
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)
par(mfrow = c(1,1))
data01$male = factor(data01$male)
data01$hsl = as.numeric(data01$hsl)
data01$cc = as.numeric(data01$cc)
data01$use = as.numeric(data01$use)
data01$msc = as.numeric(data01$msc)
data01$mas = as.numeric(data01$mas)
data01$mse = as.numeric(data01$mse)
data01$perf = as.numeric(data01$perf)
#EXAMPLE OF PREDICTIVE MEAN MATCHING USING THREE VARIABLES FOR AN ANALYSIS---------------------------
data02 = data01[c("male", "perf", "cc", "id")]
#showing extent of missing data for variables:
#proportion missing male variable:
length(which(is.na(data02$male)))/dim(data02)[1]
## [1] 0
#proportion missing perf variable:
length(which(is.na(data02$perf)))/dim(data02)[1]
## [1] 0.1714286
#proportion missing cc variable:
length(which(is.na(data02$cc)))/dim(data02)[1]
## [1] 0.1057143
#proportion missing both CC and PERF:
length(which(is.na(data02$cc) & is.na(data02$perf)))/dim(data02)[1]
## [1] 0.02285714
#PMM Example ----------------------------------------------------------------------------------------
#use a modified form of regression to come up with predicted values for all missing observations
# for each variable, the predictors can be anything (but we'll set them to be the other variables and their interaction)
current_data = data02
#list of people with missing values of perf:
missing_perf = which(is.na(current_data$perf))
missing_perf
## [1] 3 8 16 22 25 44 51 53 54 55 78 80 93 101 102 104 107
## [18] 114 116 119 120 137 139 140 141 146 152 157 170 172 174 179 195 198
## [35] 201 206 207 214 225 242 243 249 257 261 265 267 268 272 289 293 302
## [52] 305 317 319 321 324 329 333 347 350
#list of people with missing values of cc:
missing_cc = which(is.na(current_data$cc))
missing_cc
## [1] 22 50 52 53 61 76 80 96 104 128 141 151 165 166 175 178 183
## [18] 186 188 200 203 211 215 219 223 232 267 272 276 291 304 309 341 343
## [35] 345 349 350
#step #0: fill in all missing data randomly
current_data[which(current_data$id %in% missing_perf),]$perf =
sample(x = unique(current_data[which(is.na(current_data$perf) == FALSE),]$perf),
size = length(missing_perf), replace = TRUE)
current_data[which(current_data$id %in% missing_cc),]$cc =
sample(x = unique(current_data[which(is.na(current_data$cc) == FALSE),]$cc),
size = length(missing_cc), replace = TRUE)
#create all interaction terms (and ensure male is a number not a factor)
current_data$male = as.numeric(current_data$male)
current_data$maleXcc = current_data$male*current_data$cc
current_data$maleXperf = current_data$male*current_data$perf
#save beta estimates to show changes over chain
beta_perf = NULL
#step #1: initial prediction for PERF variable
perf_model_init = lm(perf ~ male + cc + male*cc, data=current_data)
beta_perf = rbind(beta_perf, t(perf_model_init$coef))
#step #2: generate betas from posterior distribution (using MVN and asymptotic values)
perf_model_meanvec = perf_model_init$coefficients
perf_model_covmat = summary(perf_model_init)$cov
perf_model_betas = rmvnorm(n = 1, mean = perf_model_meanvec, sigma = perf_model_covmat)
#step #3: using randomly generated betas, create predicted values for all people with complete predictors:
#create data matrix with columns that only have predictors in model:
data_matrix = data.matrix(current_data[c("male", "cc", "maleXcc")])
#add column of ones for intercept:
data_matrix = cbind(matrix(1, nrow = dim(data_matrix)[1], ncol = 1), data_matrix)
#make model predictions:
perf_model_predictions = data_matrix %*% t(perf_model_betas)
#step #4: for each data point with a missing value on PERF and a predicted value, find the closest predicted values:
id=1
for (id in 1:length(missing_perf)){
#for first person, find predicted perf value
missing_perf1_predicted = perf_model_predictions[missing_perf[id],1]
#from other predicted values, find five closest values to this person's perf
close_preds_perf = abs(perf_model_predictions - missing_perf1_predicted)
#add ID number to vector to identify cases that are closest:
close_preds_perf = cbind(close_preds_perf, matrix(1:dim(perf_model_predictions)[1],
nrow = dim(data_matrix)[1], ncol = 1))
#order by absolute difference
close_preds_perf = close_preds_perf[order(close_preds_perf[,1]),]
top5_perf = unique(close_preds_perf[,1])[1:5]
#take top 5 closest predicted means:
close_preds_ID = close_preds_perf[which(close_preds_perf[,1] %in% top5_perf),2]
#randomly select ID and take PERF value that matches
selectedID = sample(x = close_preds_ID, size = 1)
#fill in missing data (and interaction term)
current_data[missing_perf[id],]$perf = current_data[which(current_data$id == selectedID),]$perf
}
current_data$maleXperf = current_data$male*current_data$perf
#INITIAL SAMPLE FOR USE:
#save beta estimates to show changes over chain
beta_cc = NULL
#step #1: initial prediction for CC variable
cc_model_init = lm(cc ~ male + perf + male*perf, data=current_data)
beta_cc = rbind(beta_cc, t(cc_model_init$coef))
#step #2: generate betas from posterior distribution (using MVN and asymptotic values)
cc_model_meanvec = cc_model_init$coefficients
cc_model_covmat = summary(cc_model_init)$cov
cc_model_betas = rmvnorm(n = 1, mean = cc_model_meanvec, sigma = cc_model_covmat)
#step #3: using randomly generated betas, create predicted values for all people with complete predictors:
#create data matrix with columns that only have predictors in model:
data_matrix = data.matrix(current_data[c("male", "perf", "maleXperf")])
#add column of ones for intercept:
data_matrix = cbind(matrix(1, nrow = dim(data_matrix)[1], ncol = 1), data_matrix)
#make model predictions:
cc_model_predictions = data_matrix %*% t(cc_model_betas)
#step #4: for each data point with a missing value on PERF and a predicted value, find the closest predicted values:
id=1
for (id in 1:length(missing_cc)){
#for first person, find predicted perf value
missing_cc1_predicted = cc_model_predictions[missing_cc[id],1]
#from other predicted values, find five closest values to this person's perf
close_preds_cc = abs(cc_model_predictions - missing_cc1_predicted)
#add ID number to vector to identify cases that are closest:
close_preds_cc = cbind(close_preds_cc, matrix(1:dim(cc_model_predictions)[1],
nrow = dim(data_matrix)[1], ncol = 1))
#order by absolute difference
close_preds_cc = close_preds_cc[order(close_preds_cc[,1]),]
top5_cc = unique(close_preds_cc[,1])[1:5]
#take top 5 closest predicted means:
close_preds_ID = close_preds_cc[which(close_preds_cc[,1] %in% top5_cc),2]
#randomly select ID and take PERF value that matches
selectedID = sample(x = close_preds_ID, size = 1)
#fill in missing data (and interaction term)
current_data[missing_cc[id],]$cc = current_data[which(current_data$id == selectedID),]$cc
}
#recalculate interaction term
current_data$ccXmale = current_data$male*current_data$cc
#step #1: initial prediction for PERF variable
perf_model_2 = lm(perf ~ male + cc + male*cc, data=current_data)
beta_perf = rbind(beta_perf, t(perf_model_2$coef))
beta_perf
## (Intercept) male cc male:cc
## [1,] 13.31925 -0.2918527 0.00733972 0.05997379
## [2,] 13.29318 -0.2301773 0.04193476 0.03633290
#running MICE for data imputation (100 samples from 20 iterations):
data03 = mice(data=data01, m = 100, maxit = 20, diagnostics = TRUE)
##
## iter imp variable
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## 16 93 hsl cc use msc mas mse perf
## 16 94 hsl cc use msc mas mse perf
## 16 95 hsl cc use msc mas mse perf
## 16 96 hsl cc use msc mas mse perf
## 16 97 hsl cc use msc mas mse perf
## 16 98 hsl cc use msc mas mse perf
## 16 99 hsl cc use msc mas mse perf
## 16 100 hsl cc use msc mas mse perf
## 17 1 hsl cc use msc mas mse perf
## 17 2 hsl cc use msc mas mse perf
## 17 3 hsl cc use msc mas mse perf
## 17 4 hsl cc use msc mas mse perf
## 17 5 hsl cc use msc mas mse perf
## 17 6 hsl cc use msc mas mse perf
## 17 7 hsl cc use msc mas mse perf
## 17 8 hsl cc use msc mas mse perf
## 17 9 hsl cc use msc mas mse perf
## 17 10 hsl cc use msc mas mse perf
## 17 11 hsl cc use msc mas mse perf
## 17 12 hsl cc use msc mas mse perf
## 17 13 hsl cc use msc mas mse perf
## 17 14 hsl cc use msc mas mse perf
## 17 15 hsl cc use msc mas mse perf
## 17 16 hsl cc use msc mas mse perf
## 17 17 hsl cc use msc mas mse perf
## 17 18 hsl cc use msc mas mse perf
## 17 19 hsl cc use msc mas mse perf
## 17 20 hsl cc use msc mas mse perf
## 17 21 hsl cc use msc mas mse perf
## 17 22 hsl cc use msc mas mse perf
## 17 23 hsl cc use msc mas mse perf
## 17 24 hsl cc use msc mas mse perf
## 17 25 hsl cc use msc mas mse perf
## 17 26 hsl cc use msc mas mse perf
## 17 27 hsl cc use msc mas mse perf
## 17 28 hsl cc use msc mas mse perf
## 17 29 hsl cc use msc mas mse perf
## 17 30 hsl cc use msc mas mse perf
## 17 31 hsl cc use msc mas mse perf
## 17 32 hsl cc use msc mas mse perf
## 17 33 hsl cc use msc mas mse perf
## 17 34 hsl cc use msc mas mse perf
## 17 35 hsl cc use msc mas mse perf
## 17 36 hsl cc use msc mas mse perf
## 17 37 hsl cc use msc mas mse perf
## 17 38 hsl cc use msc mas mse perf
## 17 39 hsl cc use msc mas mse perf
## 17 40 hsl cc use msc mas mse perf
## 17 41 hsl cc use msc mas mse perf
## 17 42 hsl cc use msc mas mse perf
## 17 43 hsl cc use msc mas mse perf
## 17 44 hsl cc use msc mas mse perf
## 17 45 hsl cc use msc mas mse perf
## 17 46 hsl cc use msc mas mse perf
## 17 47 hsl cc use msc mas mse perf
## 17 48 hsl cc use msc mas mse perf
## 17 49 hsl cc use msc mas mse perf
## 17 50 hsl cc use msc mas mse perf
## 17 51 hsl cc use msc mas mse perf
## 17 52 hsl cc use msc mas mse perf
## 17 53 hsl cc use msc mas mse perf
## 17 54 hsl cc use msc mas mse perf
## 17 55 hsl cc use msc mas mse perf
## 17 56 hsl cc use msc mas mse perf
## 17 57 hsl cc use msc mas mse perf
## 17 58 hsl cc use msc mas mse perf
## 17 59 hsl cc use msc mas mse perf
## 17 60 hsl cc use msc mas mse perf
## 17 61 hsl cc use msc mas mse perf
## 17 62 hsl cc use msc mas mse perf
## 17 63 hsl cc use msc mas mse perf
## 17 64 hsl cc use msc mas mse perf
## 17 65 hsl cc use msc mas mse perf
## 17 66 hsl cc use msc mas mse perf
## 17 67 hsl cc use msc mas mse perf
## 17 68 hsl cc use msc mas mse perf
## 17 69 hsl cc use msc mas mse perf
## 17 70 hsl cc use msc mas mse perf
## 17 71 hsl cc use msc mas mse perf
## 17 72 hsl cc use msc mas mse perf
## 17 73 hsl cc use msc mas mse perf
## 17 74 hsl cc use msc mas mse perf
## 17 75 hsl cc use msc mas mse perf
## 17 76 hsl cc use msc mas mse perf
## 17 77 hsl cc use msc mas mse perf
## 17 78 hsl cc use msc mas mse perf
## 17 79 hsl cc use msc mas mse perf
## 17 80 hsl cc use msc mas mse perf
## 17 81 hsl cc use msc mas mse perf
## 17 82 hsl cc use msc mas mse perf
## 17 83 hsl cc use msc mas mse perf
## 17 84 hsl cc use msc mas mse perf
## 17 85 hsl cc use msc mas mse perf
## 17 86 hsl cc use msc mas mse perf
## 17 87 hsl cc use msc mas mse perf
## 17 88 hsl cc use msc mas mse perf
## 17 89 hsl cc use msc mas mse perf
## 17 90 hsl cc use msc mas mse perf
## 17 91 hsl cc use msc mas mse perf
## 17 92 hsl cc use msc mas mse perf
## 17 93 hsl cc use msc mas mse perf
## 17 94 hsl cc use msc mas mse perf
## 17 95 hsl cc use msc mas mse perf
## 17 96 hsl cc use msc mas mse perf
## 17 97 hsl cc use msc mas mse perf
## 17 98 hsl cc use msc mas mse perf
## 17 99 hsl cc use msc mas mse perf
## 17 100 hsl cc use msc mas mse perf
## 18 1 hsl cc use msc mas mse perf
## 18 2 hsl cc use msc mas mse perf
## 18 3 hsl cc use msc mas mse perf
## 18 4 hsl cc use msc mas mse perf
## 18 5 hsl cc use msc mas mse perf
## 18 6 hsl cc use msc mas mse perf
## 18 7 hsl cc use msc mas mse perf
## 18 8 hsl cc use msc mas mse perf
## 18 9 hsl cc use msc mas mse perf
## 18 10 hsl cc use msc mas mse perf
## 18 11 hsl cc use msc mas mse perf
## 18 12 hsl cc use msc mas mse perf
## 18 13 hsl cc use msc mas mse perf
## 18 14 hsl cc use msc mas mse perf
## 18 15 hsl cc use msc mas mse perf
## 18 16 hsl cc use msc mas mse perf
## 18 17 hsl cc use msc mas mse perf
## 18 18 hsl cc use msc mas mse perf
## 18 19 hsl cc use msc mas mse perf
## 18 20 hsl cc use msc mas mse perf
## 18 21 hsl cc use msc mas mse perf
## 18 22 hsl cc use msc mas mse perf
## 18 23 hsl cc use msc mas mse perf
## 18 24 hsl cc use msc mas mse perf
## 18 25 hsl cc use msc mas mse perf
## 18 26 hsl cc use msc mas mse perf
## 18 27 hsl cc use msc mas mse perf
## 18 28 hsl cc use msc mas mse perf
## 18 29 hsl cc use msc mas mse perf
## 18 30 hsl cc use msc mas mse perf
## 18 31 hsl cc use msc mas mse perf
## 18 32 hsl cc use msc mas mse perf
## 18 33 hsl cc use msc mas mse perf
## 18 34 hsl cc use msc mas mse perf
## 18 35 hsl cc use msc mas mse perf
## 18 36 hsl cc use msc mas mse perf
## 18 37 hsl cc use msc mas mse perf
## 18 38 hsl cc use msc mas mse perf
## 18 39 hsl cc use msc mas mse perf
## 18 40 hsl cc use msc mas mse perf
## 18 41 hsl cc use msc mas mse perf
## 18 42 hsl cc use msc mas mse perf
## 18 43 hsl cc use msc mas mse perf
## 18 44 hsl cc use msc mas mse perf
## 18 45 hsl cc use msc mas mse perf
## 18 46 hsl cc use msc mas mse perf
## 18 47 hsl cc use msc mas mse perf
## 18 48 hsl cc use msc mas mse perf
## 18 49 hsl cc use msc mas mse perf
## 18 50 hsl cc use msc mas mse perf
## 18 51 hsl cc use msc mas mse perf
## 18 52 hsl cc use msc mas mse perf
## 18 53 hsl cc use msc mas mse perf
## 18 54 hsl cc use msc mas mse perf
## 18 55 hsl cc use msc mas mse perf
## 18 56 hsl cc use msc mas mse perf
## 18 57 hsl cc use msc mas mse perf
## 18 58 hsl cc use msc mas mse perf
## 18 59 hsl cc use msc mas mse perf
## 18 60 hsl cc use msc mas mse perf
## 18 61 hsl cc use msc mas mse perf
## 18 62 hsl cc use msc mas mse perf
## 18 63 hsl cc use msc mas mse perf
## 18 64 hsl cc use msc mas mse perf
## 18 65 hsl cc use msc mas mse perf
## 18 66 hsl cc use msc mas mse perf
## 18 67 hsl cc use msc mas mse perf
## 18 68 hsl cc use msc mas mse perf
## 18 69 hsl cc use msc mas mse perf
## 18 70 hsl cc use msc mas mse perf
## 18 71 hsl cc use msc mas mse perf
## 18 72 hsl cc use msc mas mse perf
## 18 73 hsl cc use msc mas mse perf
## 18 74 hsl cc use msc mas mse perf
## 18 75 hsl cc use msc mas mse perf
## 18 76 hsl cc use msc mas mse perf
## 18 77 hsl cc use msc mas mse perf
## 18 78 hsl cc use msc mas mse perf
## 18 79 hsl cc use msc mas mse perf
## 18 80 hsl cc use msc mas mse perf
## 18 81 hsl cc use msc mas mse perf
## 18 82 hsl cc use msc mas mse perf
## 18 83 hsl cc use msc mas mse perf
## 18 84 hsl cc use msc mas mse perf
## 18 85 hsl cc use msc mas mse perf
## 18 86 hsl cc use msc mas mse perf
## 18 87 hsl cc use msc mas mse perf
## 18 88 hsl cc use msc mas mse perf
## 18 89 hsl cc use msc mas mse perf
## 18 90 hsl cc use msc mas mse perf
## 18 91 hsl cc use msc mas mse perf
## 18 92 hsl cc use msc mas mse perf
## 18 93 hsl cc use msc mas mse perf
## 18 94 hsl cc use msc mas mse perf
## 18 95 hsl cc use msc mas mse perf
## 18 96 hsl cc use msc mas mse perf
## 18 97 hsl cc use msc mas mse perf
## 18 98 hsl cc use msc mas mse perf
## 18 99 hsl cc use msc mas mse perf
## 18 100 hsl cc use msc mas mse perf
## 19 1 hsl cc use msc mas mse perf
## 19 2 hsl cc use msc mas mse perf
## 19 3 hsl cc use msc mas mse perf
## 19 4 hsl cc use msc mas mse perf
## 19 5 hsl cc use msc mas mse perf
## 19 6 hsl cc use msc mas mse perf
## 19 7 hsl cc use msc mas mse perf
## 19 8 hsl cc use msc mas mse perf
## 19 9 hsl cc use msc mas mse perf
## 19 10 hsl cc use msc mas mse perf
## 19 11 hsl cc use msc mas mse perf
## 19 12 hsl cc use msc mas mse perf
## 19 13 hsl cc use msc mas mse perf
## 19 14 hsl cc use msc mas mse perf
## 19 15 hsl cc use msc mas mse perf
## 19 16 hsl cc use msc mas mse perf
## 19 17 hsl cc use msc mas mse perf
## 19 18 hsl cc use msc mas mse perf
## 19 19 hsl cc use msc mas mse perf
## 19 20 hsl cc use msc mas mse perf
## 19 21 hsl cc use msc mas mse perf
## 19 22 hsl cc use msc mas mse perf
## 19 23 hsl cc use msc mas mse perf
## 19 24 hsl cc use msc mas mse perf
## 19 25 hsl cc use msc mas mse perf
## 19 26 hsl cc use msc mas mse perf
## 19 27 hsl cc use msc mas mse perf
## 19 28 hsl cc use msc mas mse perf
## 19 29 hsl cc use msc mas mse perf
## 19 30 hsl cc use msc mas mse perf
## 19 31 hsl cc use msc mas mse perf
## 19 32 hsl cc use msc mas mse perf
## 19 33 hsl cc use msc mas mse perf
## 19 34 hsl cc use msc mas mse perf
## 19 35 hsl cc use msc mas mse perf
## 19 36 hsl cc use msc mas mse perf
## 19 37 hsl cc use msc mas mse perf
## 19 38 hsl cc use msc mas mse perf
## 19 39 hsl cc use msc mas mse perf
## 19 40 hsl cc use msc mas mse perf
## 19 41 hsl cc use msc mas mse perf
## 19 42 hsl cc use msc mas mse perf
## 19 43 hsl cc use msc mas mse perf
## 19 44 hsl cc use msc mas mse perf
## 19 45 hsl cc use msc mas mse perf
## 19 46 hsl cc use msc mas mse perf
## 19 47 hsl cc use msc mas mse perf
## 19 48 hsl cc use msc mas mse perf
## 19 49 hsl cc use msc mas mse perf
## 19 50 hsl cc use msc mas mse perf
## 19 51 hsl cc use msc mas mse perf
## 19 52 hsl cc use msc mas mse perf
## 19 53 hsl cc use msc mas mse perf
## 19 54 hsl cc use msc mas mse perf
## 19 55 hsl cc use msc mas mse perf
## 19 56 hsl cc use msc mas mse perf
## 19 57 hsl cc use msc mas mse perf
## 19 58 hsl cc use msc mas mse perf
## 19 59 hsl cc use msc mas mse perf
## 19 60 hsl cc use msc mas mse perf
## 19 61 hsl cc use msc mas mse perf
## 19 62 hsl cc use msc mas mse perf
## 19 63 hsl cc use msc mas mse perf
## 19 64 hsl cc use msc mas mse perf
## 19 65 hsl cc use msc mas mse perf
## 19 66 hsl cc use msc mas mse perf
## 19 67 hsl cc use msc mas mse perf
## 19 68 hsl cc use msc mas mse perf
## 19 69 hsl cc use msc mas mse perf
## 19 70 hsl cc use msc mas mse perf
## 19 71 hsl cc use msc mas mse perf
## 19 72 hsl cc use msc mas mse perf
## 19 73 hsl cc use msc mas mse perf
## 19 74 hsl cc use msc mas mse perf
## 19 75 hsl cc use msc mas mse perf
## 19 76 hsl cc use msc mas mse perf
## 19 77 hsl cc use msc mas mse perf
## 19 78 hsl cc use msc mas mse perf
## 19 79 hsl cc use msc mas mse perf
## 19 80 hsl cc use msc mas mse perf
## 19 81 hsl cc use msc mas mse perf
## 19 82 hsl cc use msc mas mse perf
## 19 83 hsl cc use msc mas mse perf
## 19 84 hsl cc use msc mas mse perf
## 19 85 hsl cc use msc mas mse perf
## 19 86 hsl cc use msc mas mse perf
## 19 87 hsl cc use msc mas mse perf
## 19 88 hsl cc use msc mas mse perf
## 19 89 hsl cc use msc mas mse perf
## 19 90 hsl cc use msc mas mse perf
## 19 91 hsl cc use msc mas mse perf
## 19 92 hsl cc use msc mas mse perf
## 19 93 hsl cc use msc mas mse perf
## 19 94 hsl cc use msc mas mse perf
## 19 95 hsl cc use msc mas mse perf
## 19 96 hsl cc use msc mas mse perf
## 19 97 hsl cc use msc mas mse perf
## 19 98 hsl cc use msc mas mse perf
## 19 99 hsl cc use msc mas mse perf
## 19 100 hsl cc use msc mas mse perf
## 20 1 hsl cc use msc mas mse perf
## 20 2 hsl cc use msc mas mse perf
## 20 3 hsl cc use msc mas mse perf
## 20 4 hsl cc use msc mas mse perf
## 20 5 hsl cc use msc mas mse perf
## 20 6 hsl cc use msc mas mse perf
## 20 7 hsl cc use msc mas mse perf
## 20 8 hsl cc use msc mas mse perf
## 20 9 hsl cc use msc mas mse perf
## 20 10 hsl cc use msc mas mse perf
## 20 11 hsl cc use msc mas mse perf
## 20 12 hsl cc use msc mas mse perf
## 20 13 hsl cc use msc mas mse perf
## 20 14 hsl cc use msc mas mse perf
## 20 15 hsl cc use msc mas mse perf
## 20 16 hsl cc use msc mas mse perf
## 20 17 hsl cc use msc mas mse perf
## 20 18 hsl cc use msc mas mse perf
## 20 19 hsl cc use msc mas mse perf
## 20 20 hsl cc use msc mas mse perf
## 20 21 hsl cc use msc mas mse perf
## 20 22 hsl cc use msc mas mse perf
## 20 23 hsl cc use msc mas mse perf
## 20 24 hsl cc use msc mas mse perf
## 20 25 hsl cc use msc mas mse perf
## 20 26 hsl cc use msc mas mse perf
## 20 27 hsl cc use msc mas mse perf
## 20 28 hsl cc use msc mas mse perf
## 20 29 hsl cc use msc mas mse perf
## 20 30 hsl cc use msc mas mse perf
## 20 31 hsl cc use msc mas mse perf
## 20 32 hsl cc use msc mas mse perf
## 20 33 hsl cc use msc mas mse perf
## 20 34 hsl cc use msc mas mse perf
## 20 35 hsl cc use msc mas mse perf
## 20 36 hsl cc use msc mas mse perf
## 20 37 hsl cc use msc mas mse perf
## 20 38 hsl cc use msc mas mse perf
## 20 39 hsl cc use msc mas mse perf
## 20 40 hsl cc use msc mas mse perf
## 20 41 hsl cc use msc mas mse perf
## 20 42 hsl cc use msc mas mse perf
## 20 43 hsl cc use msc mas mse perf
## 20 44 hsl cc use msc mas mse perf
## 20 45 hsl cc use msc mas mse perf
## 20 46 hsl cc use msc mas mse perf
## 20 47 hsl cc use msc mas mse perf
## 20 48 hsl cc use msc mas mse perf
## 20 49 hsl cc use msc mas mse perf
## 20 50 hsl cc use msc mas mse perf
## 20 51 hsl cc use msc mas mse perf
## 20 52 hsl cc use msc mas mse perf
## 20 53 hsl cc use msc mas mse perf
## 20 54 hsl cc use msc mas mse perf
## 20 55 hsl cc use msc mas mse perf
## 20 56 hsl cc use msc mas mse perf
## 20 57 hsl cc use msc mas mse perf
## 20 58 hsl cc use msc mas mse perf
## 20 59 hsl cc use msc mas mse perf
## 20 60 hsl cc use msc mas mse perf
## 20 61 hsl cc use msc mas mse perf
## 20 62 hsl cc use msc mas mse perf
## 20 63 hsl cc use msc mas mse perf
## 20 64 hsl cc use msc mas mse perf
## 20 65 hsl cc use msc mas mse perf
## 20 66 hsl cc use msc mas mse perf
## 20 67 hsl cc use msc mas mse perf
## 20 68 hsl cc use msc mas mse perf
## 20 69 hsl cc use msc mas mse perf
## 20 70 hsl cc use msc mas mse perf
## 20 71 hsl cc use msc mas mse perf
## 20 72 hsl cc use msc mas mse perf
## 20 73 hsl cc use msc mas mse perf
## 20 74 hsl cc use msc mas mse perf
## 20 75 hsl cc use msc mas mse perf
## 20 76 hsl cc use msc mas mse perf
## 20 77 hsl cc use msc mas mse perf
## 20 78 hsl cc use msc mas mse perf
## 20 79 hsl cc use msc mas mse perf
## 20 80 hsl cc use msc mas mse perf
## 20 81 hsl cc use msc mas mse perf
## 20 82 hsl cc use msc mas mse perf
## 20 83 hsl cc use msc mas mse perf
## 20 84 hsl cc use msc mas mse perf
## 20 85 hsl cc use msc mas mse perf
## 20 86 hsl cc use msc mas mse perf
## 20 87 hsl cc use msc mas mse perf
## 20 88 hsl cc use msc mas mse perf
## 20 89 hsl cc use msc mas mse perf
## 20 90 hsl cc use msc mas mse perf
## 20 91 hsl cc use msc mas mse perf
## 20 92 hsl cc use msc mas mse perf
## 20 93 hsl cc use msc mas mse perf
## 20 94 hsl cc use msc mas mse perf
## 20 95 hsl cc use msc mas mse perf
## 20 96 hsl cc use msc mas mse perf
## 20 97 hsl cc use msc mas mse perf
## 20 98 hsl cc use msc mas mse perf
## 20 99 hsl cc use msc mas mse perf
## 20 100 hsl cc use msc mas mse perf
#showing distribution of imputed values for first missing observation:
hist(as.numeric(data03$imp$perf[1,]))
![](data:image/png;base64,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)
hist(as.numeric(data03$imp$cc[1,]))
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)
#using MICE functions to estimate a linear regression predicting PERF from CC, MALE and CC*MALE
model01 = with(data03, lm(perf ~ male + cc + male*cc))
#using MICE functions to pool estimates
model01ests = pool(model01)
summary(model01ests)
## est se t df Pr(>|t|)
## (Intercept) 12.67968868 0.41205197 30.7720619 302.7989 0.000000000
## male2 -0.28157619 0.69702449 -0.4039689 272.9110 0.686551985
## cc 0.09762080 0.03310796 2.9485600 303.0194 0.003440975
## male2:cc 0.08433837 0.06130710 1.3756705 273.2098 0.170050415
## lo 95 hi 95 nmis fmi lambda
## (Intercept) 11.86884073 13.4905366 NA 0.1008085 0.09488881
## male2 -1.65380447 1.0906521 NA 0.1585593 0.15241542
## cc 0.03247018 0.1627714 37 0.1003667 0.09444848
## male2:cc -0.03635599 0.2050327 NA 0.1579937 0.15185237
#comparisong with analysis including missing data:
model02 = lm(perf ~ male + cc + male*cc, data = data01)
summary(model02)
##
## Call:
## lm(formula = perf ~ male + cc + male * cc, data = data01)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.6934 -1.9638 -0.0887 1.9113 8.4172
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.70515 0.44169 28.765 < 2e-16 ***
## male1 -0.28763 0.77496 -0.371 0.71083
## cc 0.09882 0.03546 2.787 0.00571 **
## male1:cc 0.09446 0.06725 1.405 0.16134
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.925 on 257 degrees of freedom
## (89 observations deleted due to missingness)
## Multiple R-squared: 0.07587, Adjusted R-squared: 0.06508
## F-statistic: 7.033 on 3 and 257 DF, p-value: 0.0001459