Re: By trial, or by subject?
In sci.stat.edu Rich Ulrich [EMAIL PROTECTED] wrote: : If it is some other data... When you have multiple replications, : sometimes you don't want the *mean* -- for "best single performance" : you might select maximum or minimum. Or you might consider a trimmed or in a situation where you expect an increasing trend, the final or last few obs might be best = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: By trial, or by subject?
William Dunlap at Tulane has done some research on this. Do a lit search on his name. Jeff Rasmussen Spirit of Tao Te Ching Images of Taoism http://psychology.iupui.edu/tao TAO TE CHING... the Book, the Song, the Miniseries http://www.symynet.com Zen/Tao 10 Oxherding Pictures http://psychology.iupui.edu/ox/main.htm = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: By trial, or by subject?
Hi Jim, Is it correct that you measured every subject 100 times (25 times in all 4 drugs/dose groups)? Then it might be a good idea to use a repeated measurement test. This tests takes into account that people may have a different 'base' temperature; it takes away some of the within group error and may give your test a greater power. It's easiest to use the mean of your 25 observations in the 4 groups, also because you don't seem to be interested in differences in temperature over time or something. Sky Jim Kroger heeft geschreven in bericht ... Hello, I've received some expert help here on a couple previous occasions (thanks). I have an issue bothering me, which I'd like to present to you. I'm doing a two-way, 2X2 ANOVA. Suppose I have 20 subjects, and each has 25 observations of the following types: drug1-doseA (25 for each subject) drug1-doseB ( " ) drug2-doseA drug2-doseB Each observation consists of the subject's temperature. The objective is to determine whether there is a main effect of either factor (drug type and doseage) on temperature, and whether there is an interaction between the two. My question is, should I determine an average for each subject in each of the four cells, and use this as data to put into the ANOVA, or should I put the raw trials themselves into the ANOVA? There would be 80 datapoints and 2000 data points respectively, 20 or 500 per cell. I have seen both approaches taken but never heard a satisfactory justification. It would seem they are not equivalent since the latter, having more observations, has greater power. What are the implications of each option? Thank you much, Jim = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: By trial, or by subject?
In sci.stat.edu Jim Kroger [EMAIL PROTECTED] wrote: : Hello, I've received some expert help here on a couple previous occasions : (thanks). I have an issue bothering me, which I'd like to present to you. : I'm doing a two-way, 2X2 ANOVA. Suppose I have 20 subjects, and each has : 25 observations of the following types: no matter how you do it the proper analysis will be equivalent to using submect means. adding a replication factor would permit other tests (which you are not interested in) but due to their correlation structure the tests would not be valid. = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: By trial, or by subject?
On 15 Jan 2001 17:23:11 GMT, Elliot Cramer [EMAIL PROTECTED] wrote: In sci.stat.edu Jim Kroger [EMAIL PROTECTED] wrote: : Hello, I've received some expert help here on a couple previous occasions : (thanks). I have an issue bothering me, which I'd like to present to you. : I'm doing a two-way, 2X2 ANOVA. Suppose I have 20 subjects, and each has : 25 observations of the following types: no matter how you do it the proper analysis will be equivalent to using submect means. adding a replication factor would permit other tests (which you are not interested in) but due to their correlation structure the tests would not be valid. As it was stated, Elliot nailed the first question. A valid ANOVA treats the average (sum) as its starting point. If this isn't the REAL data, then something else might be true. If those are 25 0/1 items, then you might do better to model them as logistic, or something else other than a linear sum - as someone suggested. If it is some other data... When you have multiple replications, sometimes you don't want the *mean* -- for "best single performance" you might select maximum or minimum. Or you might consider a trimmed mean. Or best consistency could be indicated by smallest SD, or the best performance over a specific range (that could be, something about the Confidence Interval). -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: By trial, or by subject?
Jim, a few comments in addition to those made by other respondents: On Mon, 15 Jan 2001, Jim Kroger wrote in part: I'm doing a two-way, 2X2 ANOVA. Suppose I have 20 subjects, and each has 25 observations of the following types: drug1-doseA (25 for each subject) drug1-doseB ( " ) drug2-doseA drug2-doseB You have not stated how many subjects (Ss) receive each drug/dose combination. If all 20 Ss receive all 4 combinations, as implied by your assertion of 80 data points (below), then the design is not completely given: you must also have a factor representing the order in which the combinations were encountered by each S. If all Ss got the various drug/dose combinations in the same order, you have no way of telling whether (e.g.) the first combination affected responses to the later combinations, nor even in which direction. Also in this case, as one other respondent pointed out, you have a repeated-measures design: that is, instead of S(G x E) as in the usual 2-way ANOVA (using S for Subjects, G for druG, E for dosE), you have S x G x E, which implies (inter alia) different error terms for G, E, and GE. (In that notation, using R for the raw data values within each S, the two designs above would be R(S(B x E) and R(S) x G x E . As remarked below, the same ratios of mean squares are computed, whether R is explicitly accounted for in the design or not.) ... The objective is to determine whether there is a main effect of either factor (drug type and doseage) on temperature, and whether there is an interaction between the two. My question is, should I determine an average for each subject in each of the four cells, and use this as data to put into the ANOVA, or should I put the raw trials themselves into the ANOVA? As others have pointed out, it makes no difference. Your hypotheses are tested by comparisons among the cell means, and the denominator mean square for each hypothesis will be the estimated sampling variance of the means in question. Whether you use the mean of 25 trials for each S, or the 25 raw trials themselves, you get the same numbers. There would be 80 datapoints and 2000 data points respectively, 20 or 500 per cell. I have seen both approaches taken but never heard a satisfactory justification. It would seem they are not equivalent since the latter, having more observations, has greater power. As remarked above, this is not true. One has the same numerical estimates, and the same numbers of degrees of freedom in numerator and denominator, for each hypothesis test. As other respondents have mentioned, if the raw data are a 0/1 dichotomy, there may be an advantage in using a logistic rather than a normal model; but if the proportions (the several cell means) are not very close to 0 or 1, say between .25 and .75, there will not be much difference in the results of the analysis. -- Donald F. Burrill[EMAIL PROTECTED] 348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED] MSC #29, Plymouth, NH 03264 (603) 535-2597 Department of Mathematics, Boston University[EMAIL PROTECTED] 111 Cummington Street, room 261, Boston, MA 02215 (617) 353-5288 184 Nashua Road, Bedford, NH 03110 (603) 471-7128 = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
