Sleuth3 (version 0.1-8)

case0501: Diet Restriction and Longevity

Description

Female mice were randomly assigned to six treatment groups to investigate whether restricting dietary intake increases life expectancy. Diet treatments were:

1. "NP"---mice ate unlimited amount of nonpurified, standard diet
2. "N/N85"---mice fed normally before and after weaning. After weaning, ration was controlled at 85 kcal/wk
3. "N/R50"---normal diet before weaning and reduced calorie diet (50 kcal/wk) after weaning
4. "R/R50"---reduced calorie diet of 50 kcal/wk both before and after weaning
5. "N/R50 lopro"---normal diet before weaning, restricted diet (50 kcal/wk) after weaning and dietary protein content decreased with advancing age
6. "N/R40"---normal diet before weaning and reduced diet (40 Kcal/wk) after weaning.

Usage

case0501

source

Ramsey, F.L. and Schafer, D.W. (2013). The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed), Cengage Learning.

References

Weindruch, R., Walford, R.L., Fligiel, S. and Guthrie D. (1986). The Retardation of Aging in Mice by Dietary Restriction: Longevity, Cancer, Immunity and Lifetime Energy Intake, Journal of Nutrition 116(4):641--54.

Examples

str(case0501)
attach(case0501)

# Re-order levels for better boxplot organization: 
myDiet  <- factor(Diet, levels=c("NP","N/N85","N/R50","R/R50","lopro","N/R40") ) 
 
myNames <- c("NP(49)","N/N85(57)","N/R50(71)","R/R50(56)","lopro(56)",
  "N/R40(60)")   # Make these for boxplot labeling.
boxplot(Lifetime ~ myDiet, ylab= "Lifetime (months)", names=myNames, 
  xlab="Treatment (and sample size)") 
myAov1   <- aov(Lifetime ~ Diet) # One-way analysis of variance
plot(myAov1, which=1) # Plot residuals versus estimated means.
summary(myAov1) 
pairwise.t.test(Lifetime,Diet, pool.SD=TRUE, p.adj="none") # All t-tests

## p-VALUES AND CONFIDENCE INTERVALS FOR SPECIFIED COMPARISONS OF MEANS
if(require(multcomp)){
  diet    <- factor(Diet,labels=c("NN85", "NR40", "NR50", "NP", "RR50", "lopro")) 
  myAov2  <- aov(Lifetime ~ diet - 1) 
  myComparisons <- glht(myAov2,
          linfct=c("dietNR50 - dietNN85 = 0", 
          "dietRR50  - dietNR50 = 0",
          "dietNR40  - dietNR50 = 0",
          "dietlopro - dietNR50 = 0",
          "dietNN85  - dietNP   = 0")   ) 
  summary(myComparisons,test=adjusted("none")) # No multiple comparison adjust.
  confint(myComparisons, calpha = univariate_calpha()) # No adjustment
}

## EXAMPLE 5: BOXPLOTS FOR PRESENTATION  
boxplot(Lifetime ~ myDiet, ylab= "Lifetime (months)", names=myNames,
  main= "Lifetimes of Mice on 6 Diet Regimens",
  xlab="Diet (and sample size)", col="green", boxlwd=2, medlwd=2, whisklty=1, 
  whisklwd=2, staplewex=.2, staplelwd=2, outlwd=2, outpch=21, outbg="green", 
  outcex=1.5)   
                
detach(case0501)