Difference between revisions of "Regression Exercise"

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(Regression exercise)
(Regression exercise)
 
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  load("dbp.R")
 
  load("dbp.R")
  ls()<br data-attributes="%20/" />dbp[1:5,]<br data-attributes="%20/" />#<br data-attributes="%20/" />result.snp12 = glm (affection ~ rs1112, family=binomial("logit"), data=dbp)<br data-attributes="%20/" />print (result.snp12)<br data-attributes="%20/" />print ( class (result.snp12) )<br data-attributes="%20/" />print ( summary(result.snp12) )<br data-attributes="%20/" />#<br data-attributes="%20/" />dev.geno = anova (result.snp12, test="Chi")<br data-attributes="%20/" />lrt.pvalue = pchisq(dev.geno[dim(dev.geno)[1],"Deviance"],<br data-attributes="%20/" /> df=2, ncp=0, FALSE)<br data-attributes="%20/" />print ( lrt.pvalue )<br data-attributes="%20/" />#<br data-attributes="%20/" />print ( summary(result.snp12)$coefficients )<br data-attributes="%20/" />snp.beta = summary(result.snp12)$coefficients[2:3,1]<br data-attributes="%20/" />print ( snp.beta )<br data-attributes="%20/" />print ( exp(snp.beta) )<br data-attributes="%20/" />ci = confint (result.snp12)<br data-attributes="%20/" />print (ci)<br data-attributes="%20/" />print ( exp(ci) )<br data-attributes="%20/" />#<br data-attributes="%20/" />snp.data = dbp[,c("affection", "rs1112")]<br data-attributes="%20/" />summary(snp.data)<br data-attributes="%20/" />snp.data[,"rs1112"] <- as.numeric(snp.data[,"rs1112"]) - 1<br />summary(snp.data)<br data-attributes="%20/" />#<br data-attributes="%20/" />result.all = glm (affection ~ rs1112, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />dev.all = anova (result.all, test="Chi")<br data-attributes="%20/" />summary(result.all)<br data-attributes="%20/" />print(dev.all)<br data-attributes="%20/" />#<br data-attributes="%20/" />snp.data = dbp[,c("affection", "trait","sex", "age", "rs1112", "rs1117")]<br data-attributes="%20/" />summary(snp.data)<br data-attributes="%20/" />snp.data[,"rs1112"] <- as.numeric(snp.data[,"rs1112"]) - 1<br />snp.data[,"rs1117"] <- as.numeric(snp.data[,"rs1117"]) - 1
+
  ls()
  #<br data-attributes="%20/" />result.adj = glm (affection ~ sex + rs1112 , family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />#<br data-attributes="%20/" />result.adj = glm (affection ~ age + rs1112 , family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />#<br data-attributes="%20/" />result.adj = glm (affection ~ sex + age + rs1112, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />#<br data-attributes="%20/" />result.adj = glm (affection ~ rs1117 + rs1112, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />anova (result.adj, test="Chi")<br data-attributes="%20/" />result.adj = glm (affection ~ rs1112 + rs1117, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />anova (result.adj, test="Chi")<br data-attributes="%20/" />#<br data-attributes="%20/" />result.adj = lm (trait ~ rs1112, data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />result.adj = lm (trait ~ sex + rs1112, data=snp.data)<br data-attributes="%20/" />summary(result.adj)<br data-attributes="%20/" />#<br data-attributes="%20/" />result.inter = glm (affection ~ sex * rs1112, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.inter)<br data-attributes="%20/" />result.inter = glm (affection ~ age * rs1112, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.inter)<br data-attributes="%20/" />#<br data-attributes="%20/" />result.inter = glm (affection ~ rs1112 * rs1117, family=binomial("logit"),<br data-attributes="%20/" /> data=snp.data)<br data-attributes="%20/" />summary(result.inter)<br data-attributes="%20/" />#<br data-attributes="%20/" />q()
+
dbp[1:5,]
 +
#
 +
result.snp12 = glm (affection ~ rs1112, family=binomial("logit"), data=dbp)
 +
print (result.snp12)
 +
print ( class (result.snp12) )
 +
print ( summary(result.snp12) )
 +
#
 +
dev.geno = anova (result.snp12, test="Chi")
 +
lrt.pvalue = pchisq(dev.geno[dim(dev.geno)[1],"Deviance"], df=2, ncp=0, FALSE)
 +
print ( lrt.pvalue )
 +
#
 +
print ( summary(result.snp12)$coefficients )
 +
snp.beta = summary(result.snp12)$coefficients[2:3,1]
 +
print ( snp.beta )
 +
print ( exp(snp.beta) )
 +
ci = confint (result.snp12)
 +
print (ci)
 +
print ( exp(ci) )
 +
#
 +
snp.data = dbp[,c("affection", "rs1112")]
 +
summary(snp.data)
 +
snp.data[,"rs1112"] <- as.numeric(snp.data[,"rs1112"]) - 1<br />summary(snp.data)
 +
#
 +
result.all = glm (affection ~ rs1112, family=binomial("logit"), data=snp.data)
 +
dev.all = anova (result.all, test="Chi")
 +
summary(result.all)
 +
print(dev.all)
 +
#
 +
snp.data = dbp[,c("affection", "trait","sex", "age", "rs1112", "rs1117")]
 +
summary(snp.data)
 +
snp.data[,"rs1112"] <- as.numeric(snp.data[,"rs1112"]) - 1<br />snp.data[,"rs1117"] <- as.numeric(snp.data[,"rs1117"]) - 1
 +
  #
 +
result.adj = glm (affection ~ sex + rs1112 , family=binomial("logit"), data=snp.data)
 +
summary(result.adj)
 +
#
 +
result.adj = glm (affection ~ age + rs1112 , family=binomial("logit"), data=snp.data)
 +
summary(result.adj)
 +
#
 +
result.adj = glm (affection ~ sex + age + rs1112, family=binomial("logit"), data=snp.data)
 +
summary(result.adj)
 +
#
 +
result.adj = glm (affection ~ rs1117 + rs1112, family=binomial("logit"), data=snp.data)
 +
summary(result.adj)
 +
anova (result.adj, test="Chi")
 +
result.adj = glm (affection ~ rs1112 + rs1117, family=binomial("logit"), data=snp.data)
 +
summary(result.adj)
 +
anova (result.adj, test="Chi")
 +
#
 +
result.adj = lm (trait ~ rs1112, data=snp.data)
 +
summary(result.adj)
 +
result.adj = lm (trait ~ sex + rs1112, data=snp.data)
 +
summary(result.adj)
 +
#
 +
result.inter = glm (affection ~ sex * rs1112, family=binomial("logit"), data=snp.data)
 +
summary(result.inter)
 +
result.inter = glm (affection ~ age * rs1112, family=binomial("logit"), data=snp.data)
 +
summary(result.inter)
 +
#
 +
result.inter = glm (affection ~ rs1112 * rs1117, family=binomial("logit"), data=snp.data)
 +
summary(result.inter)
 +
#
 +
q()

Latest revision as of 03:30, 8 March 2017

Regression exercise

In R:

load("dbp.R")
ls()
dbp[1:5,]
#
result.snp12 = glm (affection ~ rs1112, family=binomial("logit"), data=dbp)
print (result.snp12)
print ( class (result.snp12) )
print ( summary(result.snp12) )
#
dev.geno = anova (result.snp12, test="Chi")
lrt.pvalue = pchisq(dev.geno[dim(dev.geno)[1],"Deviance"], df=2, ncp=0, FALSE)
print ( lrt.pvalue )
#
print ( summary(result.snp12)$coefficients )
snp.beta = summary(result.snp12)$coefficients[2:3,1]
print ( snp.beta )
print ( exp(snp.beta) )
ci = confint (result.snp12)
print (ci)
print ( exp(ci) )
#
snp.data = dbp[,c("affection", "rs1112")]
summary(snp.data)
snp.data[,"rs1112"] <- as.numeric(snp.data[,"rs1112"]) - 1
summary(snp.data) # result.all = glm (affection ~ rs1112, family=binomial("logit"), data=snp.data) dev.all = anova (result.all, test="Chi") summary(result.all) print(dev.all) # snp.data = dbp[,c("affection", "trait","sex", "age", "rs1112", "rs1117")] summary(snp.data) snp.data[,"rs1112"] <- as.numeric(snp.data[,"rs1112"]) - 1
snp.data[,"rs1117"] <- as.numeric(snp.data[,"rs1117"]) - 1 # result.adj = glm (affection ~ sex + rs1112 , family=binomial("logit"), data=snp.data) summary(result.adj) # result.adj = glm (affection ~ age + rs1112 , family=binomial("logit"), data=snp.data) summary(result.adj) # result.adj = glm (affection ~ sex + age + rs1112, family=binomial("logit"), data=snp.data) summary(result.adj) # result.adj = glm (affection ~ rs1117 + rs1112, family=binomial("logit"), data=snp.data) summary(result.adj) anova (result.adj, test="Chi") result.adj = glm (affection ~ rs1112 + rs1117, family=binomial("logit"), data=snp.data) summary(result.adj) anova (result.adj, test="Chi") # result.adj = lm (trait ~ rs1112, data=snp.data) summary(result.adj) result.adj = lm (trait ~ sex + rs1112, data=snp.data) summary(result.adj) # result.inter = glm (affection ~ sex * rs1112, family=binomial("logit"), data=snp.data) summary(result.inter) result.inter = glm (affection ~ age * rs1112, family=binomial("logit"), data=snp.data) summary(result.inter) # result.inter = glm (affection ~ rs1112 * rs1117, family=binomial("logit"), data=snp.data) summary(result.inter) # q()