Mice experiment: lifetime versus diet
The data for this discussion comes from the book The Statistical Sleuth, by Ramsey and Schafer (Duxbury, 1997). An experiment was conducted on female mice, which were randomly assigned to one of the following six treatment groups (as described by Ramsey and Schafer):
NOTE: This data comes from R. Weindruch, R.L. Walford, S. Fligiel, and D. Guthrie, "The Retardation of Aging in Mice by Dietary Restriction: Longevity, Cancer, Immunity and Lifetime Energy Intake," Journal of Nutrition 116(4) (1986): 641-54.
Generally the researchers' questions concerned comparisons of lifetimes between the various diets. There were specifically these questions:
These data are available as the data frame mice.df which should be
available to you automatically from my account. The data frame contains
two variables: Lifetime, which gives the lifetime of each mouse in months,
and Treatment, whose values are described above.
One-way ANOVA with R
Get the data and do basic descriptive statistics:
attach(mice.df)
summary(mice.df)
boxplot(Lifetime ~ Treatment)
nn <- tapply(Lifetime, Treatment, length)
mm <- tapply(Lifetime, Treatment, mean)
ss <- tapply(Lifetime, Treatment, sd)
round(cbind(nn,mm,ss),1)
Do the one-way ANOVA:
fm1 <-aov(Lifetime ~ Treatment) #Fit the one-way ANOVA model.
anova(fm1) #Obtain the ANOVA table.
Follow-up analysis:
pairwise.t.test(Lifetime, Treatment, p.adj="bonferroni")
Here is the Tukey analysis for the mice.short.df data.
diff lcl ucl conclusion
NN85-NP 4.90 3.29 6.51 reject
NN85-NR40 -13.94 -15.55 -12.33 reject
NN85-NR50 -9.00 -10.61 -7.39 reject
NN85-LOPRO -10.66 -12.27 -9.05 reject
NN85-RR50 -8.66 -10.27 -7.05 reject
NP-NR40 -18.84 -20.45 -17.23 reject
NP-NR50 -13.90 -15.51 -12.29 reject
NP-LOPRO -15.56 -17.17 -13.95 reject
NP-RR50 -13.56 -15.17 -11.95 reject
NR40-NR50 4.94 3.33 6.55 reject
NR40-LOPRO 3.28 1.67 4.89 reject
NR40-RR50 5.28 3.67 6.89 reject
NR50-LOPRO -1.66 -3.27 -0.05 reject
NR50-RR50 0.34 -1.27 1.95 NS
LOPRO-RR50 2.00 0.39 3.61 reject
Here is the Tukey analysis for full mice data set.
> round(cbind(nn,mm,ss),2)
nn mm ss
N/N85 57 32.69 5.13
NP 49 27.40 6.13
N/R40 60 45.12 6.70
N/R50 71 41.91 7.58
N/R50_lopro 56 42.89 6.68
R/R50 56 40.17 7.40
TukeyHSD(mice.aov)
diff lwr upr p adj
NP-N/N85 -5.2891873 -9.032153 -1.5462215 0.0008921
N/R40-N/N85 12.4254386 8.871759 15.9791182 0.0000000
N/R50-N/N85 9.2228564 5.805921 12.6397919 0.0000000
N/R50_lopro-N/N85 10.1944862 6.579504 13.8094685 0.0000000
R/R50-N/N85 7.4802005 3.865218 11.0951828 0.0000001
N/R40-NP 17.7146259 14.015169 21.4140828 0.0000000
N/R50-NP 14.5120437 10.943740 18.0803473 0.0000000
N/R50_lopro-NP 15.4836735 11.725291 19.2420560 0.0000000
R/R50-NP 12.7693878 9.011005 16.5277703 0.0000000
N/R50-N/R40 -3.2025822 -6.571801 0.1666368 0.0731183
N/R50_lopro-N/R40 -2.2309524 -5.800866 1.3389615 0.4729247
R/R50-N/R40 -4.9452381 -8.515152 -1.3753242 0.0012230
N/R50_lopro-N/R50 0.9716298 -2.462187 4.4054461 0.9654234
R/R50-N/R50 -1.7426559 -5.176472 1.6911604 0.6934788
R/R50-N/R50_lopro -2.7142857 -6.345228 0.9166568 0.2681131
mu_i mu_j Y-bar_i - Y-bar_j Signif(.05)?
---------------------------------
NN85 NP -5.29 yes
NN85 NR40 12.43 yes
NN85 NR50 9.22 yes
NN85 LOPRO 10.22 yes
NN85 RR50 7.48 yes
NP NR40 17.72 yes
NP NR50 14.51 yes
NP LOPRO 15.49 yes
NP RR50 12.77 yes
NR40 NR50 -3.21 yes
NR40 LOPRO -2.23 no
NR40 RR50 -4.95 yes
NR50 LOPRO .98 no
NR50 RR50 -1.74 no
LOPRO RR50 -2.72 no
NP NN85 RR50
NR50
LOPRO NR40
o o o o o o
___ ___ _______
_________
----|----------|----------|----------|----------|---
25 30 35 40 45
Full data set
Lifetime Treatment
1 35.5 NP
2 35.4 NP
3 34.9 NP
4 34.8 NP
5 33.8 NP
6 33.5 NP
7 32.6 NP
8 32.4 NP
9 31.8 NP
10 31.6 NP
11 31.5 NP
12 31.4 NP
13 31.4 NP
14 31.3 NP
15 30.8 NP
16 30.7 NP
17 30.5 NP
18 30.4 NP
19 30.2 NP
20 30.2 NP
21 30.1 NP
22 30.0 NP
23 29.6 NP
24 29.3 NP
25 28.9 NP
26 28.3 NP
27 28.0 NP
28 27.5 NP
29 27.3 NP
30 27.1 NP
31 26.8 NP
32 26.6 NP
33 26.5 NP
34 26.3 NP
35 25.9 NP
36 25.1 NP
37 24.8 NP
38 24.7 NP
39 24.3 NP
40 24.1 NP
41 24.0 NP
42 22.1 NP
43 21.5 NP
44 21.8 NP
45 20.0 NP
46 18.0 NP
47 13.8 NP
48 9.2 NP
49 6.4 NP
50 42.3 N/N85
51 40.1 N/N85
52 39.5 N/N85
53 38.6 N/N85
54 38.4 N/N85
55 38.3 N/N85
56 37.8 N/N85
57 37.6 N/N85
58 37.4 N/N85
59 37.3 N/N85
60 36.8 N/N85
61 36.5 N/N85
62 36.5 N/N85
63 36.5 N/N85
64 36.4 N/N85
65 35.9 N/N85
66 35.5 N/N85
67 35.5 N/N85
68 35.3 N/N85
69 35.3 N/N85
70 34.9 N/N85
71 34.6 N/N85
72 34.5 N/N85
73 34.4 N/N85
74 33.8 N/N85
75 33.5 N/N85
76 33.3 N/N85
77 33.3 N/N85
78 33.1 N/N85
79 33.0 N/N85
80 32.9 N/N85
81 32.5 N/N85
82 32.4 N/N85
83 32.3 N/N85
84 31.7 N/N85
85 31.7 N/N85
86 31.6 N/N85
87 31.6 N/N85
88 31.5 N/N85
89 33.1 N/N85
90 31.5 N/N85
91 31.4 N/N85
92 31.4 N/N85
93 31.0 N/N85
94 30.3 N/N85
95 30.1 N/N85
96 29.6 N/N85
97 29.3 N/N85
98 29.2 N/N85
99 28.8 N/N85
100 27.9 N/N85
101 24.5 N/N85
102 22.3 N/N85
103 21.9 N/N85
104 19.8 N/N85
105 19.3 N/N85
106 17.9 N/N85
107 49.7 N/R50
108 49.3 N/R50
109 48.6 N/R50
110 48.3 N/R50
111 48.0 N/R50
112 47.7 N/R50
113 47.5 N/R50
114 47.2 N/R50
115 47.1 N/R50
116 47.0 N/R50
117 47.0 N/R50
118 47.0 N/R50
119 46.9 N/R50
120 46.9 N/R50
121 46.3 N/R50
122 45.9 N/R50
123 45.9 N/R50
124 44.5 N/R50
125 44.1 N/R50
126 44.0 N/R50
127 43.6 N/R50
128 43.3 N/R50
129 42.1 N/R50
130 42.0 N/R50
131 42.0 N/R50
132 41.9 N/R50
133 41.9 N/R50
134 41.6 N/R50
135 40.5 N/R50
136 40.1 N/R50
137 39.2 N/R50
138 38.9 N/R50
139 37.4 N/R50
140 37.3 N/R50
141 36.7 N/R50
142 36.4 N/R50
143 36.2 N/R50
144 35.8 N/R50
145 35.7 N/R50
146 35.4 N/R50
147 35.3 N/R50
148 35.0 N/R50
149 35.0 N/R50
150 34.8 N/R50
151 34.7 N/R50
152 33.5 N/R50
153 32.8 N/R50
154 31.5 N/R50
155 30.8 N/R50
156 30.6 N/R50
157 29.9 N/R50
158 29.2 N/R50
159 28.0 N/R50
160 26.3 N/R50
161 24.7 N/R50
162 23.4 N/R50
163 51.9 N/R50
164 51.7 N/R50
165 51.4 N/R50
166 51.3 N/R50
167 50.9 N/R50
168 50.5 N/R50
169 50.5 N/R50
170 50.2 N/R50
171 50.0 N/R50
172 49.4 N/R50
173 49.2 N/R50
174 49.2 N/R50
175 49.1 N/R50
176 49.1 N/R50
177 49.1 N/R50
178 49.1 R/R50
179 48.7 R/R50
180 48.3 R/R50
181 48.1 R/R50
182 48.0 R/R50
183 47.8 R/R50
184 47.7 R/R50
185 47.6 R/R50
186 47.5 R/R50
187 47.3 R/R50
188 47.2 R/R50
189 46.9 R/R50
190 46.7 R/R50
191 46.5 R/R50
192 46.3 R/R50
193 45.6 R/R50
194 45.2 R/R50
195 45.1 R/R50
196 44.4 R/R50
197 43.9 R/R50
198 43.6 R/R50
199 42.9 R/R50
200 42.7 R/R50
201 42.6 R/R50
202 42.5 R/R50
203 42.4 R/R50
204 42.0 R/R50
205 41.5 R/R50
206 41.3 R/R50
207 40.9 R/R50
208 40.7 R/R50
209 40.4 R/R50
210 39.9 R/R50
211 39.4 R/R50
212 38.9 R/R50
213 38.2 R/R50
214 37.7 R/R50
215 37.6 R/R50
216 37.2 R/R50
217 35.4 R/R50
218 35.4 R/R50
219 35.2 R/R50
220 34.3 R/R50
221 32.7 R/R50
222 32.5 R/R50
223 31.8 R/R50
224 31.1 R/R50
225 30.9 R/R50
226 29.8 R/R50
227 26.8 R/R50
228 25.7 R/R50
229 25.1 R/R50
230 23.5 R/R50
231 18.6 R/R50
232 42.4 R/R50
233 48.1 R/R50
234 50.7 N/R50_lopro
235 50.6 N/R50_lopro
236 50.5 N/R50_lopro
237 50.3 N/R50_lopro
238 50.1 N/R50_lopro
239 50.1 N/R50_lopro
240 50.0 N/R50_lopro
241 50.0 N/R50_lopro
242 49.8 N/R50_lopro
243 49.7 N/R50_lopro
244 49.6 N/R50_lopro
245 49.0 N/R50_lopro
246 48.9 N/R50_lopro
247 48.5 N/R50_lopro
248 48.3 N/R50_lopro
249 48.3 N/R50_lopro
250 48.1 N/R50_lopro
251 47.7 N/R50_lopro
252 47.0 N/R50_lopro
253 46.8 N/R50_lopro
254 46.8 N/R50_lopro
255 46.8 N/R50_lopro
256 46.2 N/R50_lopro
257 46.2 N/R50_lopro
258 45.1 N/R50_lopro
259 45.0 N/R50_lopro
260 45.0 N/R50_lopro
261 44.3 N/R50_lopro
262 43.6 N/R50_lopro
263 43.1 N/R50_lopro
264 42.3 N/R50_lopro
265 42.9 N/R50_lopro
266 42.7 N/R50_lopro
267 42.4 N/R50_lopro
268 42.0 N/R50_lopro
269 41.8 N/R50_lopro
270 41.6 N/R50_lopro
271 40.6 N/R50_lopro
272 40.4 N/R50_lopro
273 39.9 N/R50_lopro
274 39.5 N/R50_lopro
275 39.2 N/R50_lopro
276 39.0 N/R50_lopro
277 38.5 N/R50_lopro
278 38.2 N/R50_lopro
279 38.0 N/R50_lopro
280 36.2 N/R50_lopro
281 36.3 N/R50_lopro
282 35.8 N/R50_lopro
283 34.0 N/R50_lopro
284 33.4 N/R50_lopro
285 32.2 N/R50_lopro
286 30.6 N/R50_lopro
287 27.5 N/R50_lopro
288 26.3 N/R50_lopro
289 24.2 N/R50_lopro
290 54.6 N/R40
291 54.0 N/R40
292 53.8 N/R40
293 53.3 N/R40
294 52.9 N/R40
295 52.7 N/R40
296 52.5 N/R40
297 52.4 N/R40
298 52.0 N/R40
299 51.8 N/R40
300 51.3 N/R40
301 51.3 N/R40
302 51.0 N/R40
303 50.8 N/R40
304 50.3 N/R40
305 50.1 N/R40
306 49.8 N/R40
307 48.7 N/R40
308 48.3 N/R40
309 48.1 N/R40
310 47.6 N/R40
311 47.6 N/R40
312 47.6 N/R40
313 47.5 N/R40
314 47.5 N/R40
315 47.5 N/R40
316 50.5 N/R40
317 47.5 N/R40
318 46.4 N/R40
319 45.3 N/R40
320 45.7 N/R40
321 44.2 N/R40
322 43.8 N/R40
323 43.8 N/R40
324 43.7 N/R40
325 43.6 N/R40
326 43.6 N/R40
327 43.3 N/R40
328 43.2 N/R40
329 43.1 N/R40
330 42.7 N/R40
331 42.7 N/R40
332 42.5 N/R40
333 42.3 N/R40
334 42.2 N/R40
335 42.2 N/R40
336 41.6 N/R40
337 40.8 N/R40
338 40.3 N/R40
339 40.0 N/R40
340 38.9 N/R40
341 37.2 N/R40
342 36.7 N/R40
343 36.6 N/R40
344 36.1 N/R40
345 33.9 N/R40
346 31.0 N/R40
347 29.4 N/R40
348 19.6 N/R40
349 47.6 N/R40