case0501: Diet Restriction and Longevity

Description Usage Format Source References Examples

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

1

Format

A data frame with 349 observations on the following 2 variables.

Lifetime

the lifetime of the mice (in months)

Diet

factor variable with six levels—"NP", "N/N85", "lopro", "N/R50", "R/R50" and "N/R40"

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

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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)

Sleuth3 documentation built on May 29, 2017, 11:28 a.m.

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