Last data update: 2014.03.03

 R: hiv
hivR Documentation

hiv

Description

A study of 47 patients with similar profiles. Measurements on cd4 and cd8 levels are displayed for each panel of patients having identical predictor profiles. Both cd4 and cd8 have three levels. The data should be modeled as a grouped logistic model, but may also be modeled as a count model depending on what a research wishes to determine from the data.

Usage

data(hiv)

Format

A data frame with 11 observations of grouped data with 4 variables.

infec

1=Patient diagnosed with HIV; 0=not diagnosed with HIV

cases

number of patients for each patient profile

cd4

3 levels: 0, 1, and 2

cd8

3 levels: 0, 1, and 2

Details

hiv is saved as a data frame.

Source

Hilbe, Practical Guide to Logistic Regression, Chapman & Hall/CRC.

References

Hilbe, Joseph M (2015), Practical Guide to Logistic Regression, Chapman & Hall/CRC.

Examples

# Not run
#data(hiv)
#table(hiv); hiv
#noinfec <- hiv$cases -  hiv$infec
#myhiv<- glm(cbind(infec, noinfec) ~  factor(cd4)  + factor#(cd8), family=binomial, data=hiv)
#summary(myhiv)
#mymodq <- glm( cbind(infec, noinfec) ~  factor(cd4)  + factor(cd8), family=quasibinomial, data=hiv)
#summary(mymodq)
#toOR(myhiv)
#End(Not run)

library(LOGIT)
data(hiv)
table(hiv); hiv
noinfec <- hiv$cases -  hiv$infec
response <- cbind(hiv$infec, noinfec)
myhiv<- glm(response ~  factor(cd4)  + factor(cd8), family=binomial, data=hiv)
summary(myhiv)

mymodq <- glm(response ~  factor(cd4)  + factor(cd8), family=quasibinomial, data=hiv)
summary(mymodq)

#library(sandwich)
#sqrt(diag(vcovHC(myhiv, type="HC0")))
toOR(myhiv)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(LOGIT)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/LOGIT/hiv.rd_%03d_medium.png", width=480, height=480)
> ### Name: hiv
> ### Title: hiv
> ### Aliases: hiv
> ### Keywords: datasets
> 
> ### ** Examples
> 
> # Not run
> #data(hiv)
> #table(hiv); hiv
> #noinfec <- hiv$cases -  hiv$infec
> #myhiv<- glm(cbind(infec, noinfec) ~  factor(cd4)  + factor#(cd8), family=binomial, data=hiv)
> #summary(myhiv)
> #mymodq <- glm( cbind(infec, noinfec) ~  factor(cd4)  + factor(cd8), family=quasibinomial, data=hiv)
> #summary(mymodq)
> #toOR(myhiv)
> #End(Not run)
> 
> library(LOGIT)
> data(hiv)
> table(hiv); hiv
, , cd4 = 0, cd8 = 0

     cases
infec 1 2 3 4 5 8 13
    0 0 0 1 0 0 0  0
    1 0 0 0 1 0 0  0

, , cd4 = 1, cd8 = 0

     cases
infec 1 2 3 4 5 8 13
    0 0 0 0 0 1 0  0
    1 0 1 0 0 0 0  0

, , cd4 = 2, cd8 = 0

     cases
infec 1 2 3 4 5 8 13
    0 0 1 0 0 0 0  0
    1 0 0 0 0 0 0  0

, , cd4 = 0, cd8 = 1

     cases
infec 1 2 3 4 5 8 13
    0 0 0 0 0 0 0  0
    1 0 0 0 0 0 0  0

, , cd4 = 1, cd8 = 1

     cases
infec 1 2 3 4 5 8 13
    0 0 0 0 0 0 1  0
    1 0 0 0 1 0 0  0

, , cd4 = 2, cd8 = 1

     cases
infec 1 2 3 4 5 8 13
    0 0 0 0 0 0 0  1
    1 0 0 0 0 0 0  0

, , cd4 = 0, cd8 = 2

     cases
infec 1 2 3 4 5 8 13
    0 0 0 0 0 0 0  0
    1 1 0 0 0 0 0  0

, , cd4 = 1, cd8 = 2

     cases
infec 1 2 3 4 5 8 13
    0 0 0 0 0 0 0  0
    1 0 1 0 0 0 0  0

, , cd4 = 2, cd8 = 2

     cases
infec 1 2 3 4 5 8 13
    0 0 1 0 0 0 0  0
    1 1 0 0 0 0 0  0

   infec cases cd4 cd8
1      0     3   0   0
2      0     8   1   1
3      0     2   2   2
4      0     5   1   0
5      0     2   2   0
6      0    13   2   1
7      1     1   0   2
8      1     2   1   2
9      1     4   0   0
10     1     4   1   1
11     1     1   2   2
12     1     2   1   0
> noinfec <- hiv$cases -  hiv$infec
> response <- cbind(hiv$infec, noinfec)
> myhiv<- glm(response ~  factor(cd4)  + factor(cd8), family=binomial, data=hiv)
> summary(myhiv)

Call:
glm(formula = response ~ factor(cd4) + factor(cd8), family = binomial, 
    data = hiv)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.1195  -1.0655  -0.4178   0.7837   1.6206  

Coefficients:
             Estimate Std. Error z value Pr(>|z|)  
(Intercept)   -1.5730     0.9518  -1.653   0.0984 .
factor(cd4)1  -0.5334     1.3709  -0.389   0.6972  
factor(cd4)2  -2.3701     1.8201  -1.302   0.1929  
factor(cd8)1  -0.4740     1.5044  -0.315   0.7527  
factor(cd8)2   2.9433     1.4680   2.005   0.0450 *
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 21.357  on 11  degrees of freedom
Residual deviance: 11.810  on  7  degrees of freedom
AIC: 28.034

Number of Fisher Scoring iterations: 5

> 
> mymodq <- glm(response ~  factor(cd4)  + factor(cd8), family=quasibinomial, data=hiv)
> summary(mymodq)

Call:
glm(formula = response ~ factor(cd4) + factor(cd8), family = quasibinomial, 
    data = hiv)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.1195  -1.0655  -0.4178   0.7837   1.6206  

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept)   -1.5730     1.2159  -1.294    0.237
factor(cd4)1  -0.5334     1.7513  -0.305    0.770
factor(cd4)2  -2.3701     2.3252  -1.019    0.342
factor(cd8)1  -0.4740     1.9219  -0.247    0.812
factor(cd8)2   2.9433     1.8754   1.569    0.161

(Dispersion parameter for quasibinomial family taken to be 1.631979)

    Null deviance: 21.357  on 11  degrees of freedom
Residual deviance: 11.810  on  7  degrees of freedom
AIC: NA

Number of Fisher Scoring iterations: 5

> 
> #library(sandwich)
> #sqrt(diag(vcovHC(myhiv, type="HC0")))
> toOR(myhiv)
                  or   delta  zscore pvalue exp.loci. exp.upci.
(Intercept)   0.2074  0.1974 -1.6526 0.0984    0.0321    1.3398
factor(cd4)1  0.5866  0.8042 -0.3891 0.6972    0.0399    8.6146
factor(cd4)2  0.0935  0.1701 -1.3022 0.1929    0.0026    3.3110
factor(cd8)1  0.6225  0.9365 -0.3151 0.7527    0.0326   11.8770
factor(cd8)2 18.9775 27.8595  2.0049 0.0450    1.0682  337.1512
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


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