Your question is much too broad for this list. It is not clear from  
your question how much statistics you know and what you have already  
done. (It also raises the concern that this may be a homework  
assignment.)

Have you tried
ox.lm <- lm(vo2 ~ speed * stride * mass, data = DATA)

But you really need a mixed model which would require you to  
understand the above in detail and then use lmer() to fit mixed  
models as in the lme4 package.

On Mar 18, 2007, at 2:07 PM, pasarah wrote:

> We are two french students and we have a problem concerning an  
> exercize.
> We don't know how to resolve it.
> It would be fantastic if someone can help us.
> Thanks.
>
> Description:
> This study examined how the metabolic cost of locomotion varied
> with speed, stride frequency and body mass. Cost was determined
> by measuring oxygen consumption (’vo2’), analyzing the oxygen
> content in air inhaled and exhaled by the subjects through a mask.
> The rate of oxgen consumption was measured for three ’subject’s
> locomoting at all combinations of low and high levels of the three
> factors - running ’speed’, ’stride’ frequency, and ’mass’
> distribution in the leg. The first factor was set using a
> treadmill, the second by synchronizing the subjects’ pace with a
> metronome, and the third by varying the positions of weights
> strapped onto the legs or waist. In addition to these three
> design factors, other variables were measured by filming each
> trial with a high-speed motion camera. Ignore these other
> measurements for this problem.
> Format:
> Running data frame with 24 observations on 13 variables.
> [,1] subject factor subject identifier
> [,2] order ordered order of treatment
> [,3] speed factor running speed
> [,4] stride numeric stride frequency
> [,5] mass numeric attached mass in g
> [,6] vo2 numeric oxygen consumption
> [,7] tm numeric time
> [,8] etot numeric etot
> [,9] cn numeric cn
> [,10] ar numeric ar
> [,11] ecn numeric ecn
> [,12] ahm numeric ahm
> [,13] vhm numeric vhm
>
> DATA
>  	subject	order	speed	stride	mass	vo2	tm	etot	cn	ar	ecn	ahm	vhm
> 1	1	4	2.68	138	W	2838	71.8	221.14	0.381	0.053	0.260	15.2	13.7
> 2	1	8	2.68	138	L	2905	71.8	221.14	0.356	0.084	0.220	16.4	13.6
> 3	1	7	2.68	146	W	2630	71.8	221.14	0.359	0.056	0.225	15.0	12.7
> 4	1	3	2.68	146	L	2696	71.8	221.14	0.351	0.061	0.225	14.2	12.4
> 5	1	1	3.13	138	W	3100	71.8	270.69	0.335	0.099	0.285	13.5	14.2
> 6	1	6	3.13	138	L	3343	71.8	270.69	0.313	0.119	0.230	16.6	14.7
> 7	1	2	3.13	146	W	3001	71.8	270.69	0.344	0.065	0.225	12.0	13.5
> 8	1	5	3.13	146	L	3079	71.8	270.69	0.314	0.095	0.200	12.1	13.3
> 9	2	2	2.68	138	W	2782	76.8	236.54	0.403	0.038	0.240	13.6	11.1
> 10	2	8	2.68	138	L	2763	76.8	236.54	0.370	0.071	0.210	15.8	12.2
> 11	2	3	2.68	146	W	2582	76.8	236.54	0.363	0.048	0.215	14.3	11.0
> 12	2	5	2.68	146	L	2619	76.8	236.54	0.343	0.073	0.215	15.0	12.3
> 13	2	6	3.13	138	W	3277	76.8	289.54	0.364	0.076	0.230	11.7	11.7
> 14	2	1	3.13	138	L	3461	76.8	289.54	0.350	0.090	0.210	11.6	12.2
> 15	2	7	3.13	146	W	3116	76.8	289.54	0.341	0.071	0.215	12.3	11.6
> 16	2	4	3.13	146	L	3154	76.8	289.54	0.316	0.099	0.215	14.6	12.8
> 17	3	4	2.68	138	W	2665	69.8	214.98	0.316	0.120	0.245	16.7	14.5
> 18	3	7	2.68	138	L	2759	69.8	214.98	0.311	0.114	0.230	15.5	13.5
> 19	3	3	2.68	146	W	2504	69.8	214.98	0.289	0.124	0.225	19.0	14.2
> 20	3	5	2.68	146	L	2537	69.8	214.98	0.290	0.118	0.240	16.7	12.3
> 21	3	2	3.13	138	W	3077	69.8	263.15	0.294	0.138	0.250	14.4	15.4
> 22	3	1	3.13	138	L	3117	69.8	263.15	0.284	0.141	0.230	15.0	14.4
> 23	3	6	3.13	146	W	2816	69.8	263.15	0.271	0.137	0.210	14.6	13.7
> 24	3	8	3.13	146	L	2966	69.8	263.15	0.286	0.128	0.250	14.7	13.4



_____________________________
Professor Michael Kubovy
University of Virginia
Department of Psychology
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