*t*-test).

Question:

Does the fact that a fractionally higher GPA was achieved across all 4 years by Group A over Group B mean anything?

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Question:

Does the fact that a fractionally higher GPA was achieved across all 4 years by Group A over Group B mean anything?

I just did a t-test for each year - the differences in the means are so snall compared to the std devs that there is no reason to believe they are due to anything but chance , in each year. (p values of roughly 0.5).

Now, the question could be, how can you get 4 years where each time group A is better then group B, by chance? The probability of that would be 1/16 = 0.06, so, that would not be significant either.

BTW it is a bit suspicious that you have EXACTLY the same nunber of participants in each group, each year. Is that really so?

regards

Or rather, what is the chance that one group will better than the other in each of 4 trials (i.e. either A > B throughout, or B < A throughout) (2/16, I suppose)?

With kind regards

K.

With kind regards

K.

I think that would be a different question. As I actually observed group A being ahead of group B in all 4 years, I would ask what the chances are of seeing A ahead of B in the absence of a systematic effect. A bit like a one-sided vs. two-sided test?

regards

hi,

...

BTW it is a bit suspicious that you have EXACTLY the same nunber of participants in each group, each year. Is that really so?

regards

...

BTW it is a bit suspicious that you have EXACTLY the same nunber of participants in each group, each year. Is that really so?

regards

It feels very UNlikely that Group A would have a (minimally) better mean value each year. The tiny difference can be dismissed for each individual year (per the t-test), but for that result to happen 4 years in a row is interesting to me. I need to address that in my findings, but I do not want to over-reach in my interpretations.... LOL.

What can I say about the fact that Group A had that higher score 4 years in a row...??

Second, If the two groups are slightly different in 2012, guess what, they are going to continue to be different, year is not independent of the prior year.

You need a baseline measure for both groups, then plot their GPA across time with 95% confidence interval to visualize the time series.

Something like the following. Also, I don't see any harm in using the full B sample, unless a priori you said you were going to use the subsample. A greater sample size will equal smaller standard errors. Just report that you ran it both ways, and the full sample was the post hoc test.

http://www.jimmunol.org/content/jimmunol/196/12/5047/F9.large.jpg?width=800&height=600&carousel=1

P.S., If these are the same student across time, there is obvious dependence, BUT, you also have to account for the attrition. Does it represent systematic bias? So if you lose people in A did you than just randomly remove people from B, if so that seem like a bad idea for sure.

I wanted to compare all "B" group students (~1,000) to the n of the A students, but was told I couldn't for this study. Those comparison stats look very similar-- would not have made a difference.

Second, If the two groups are slightly different in 2012, guess what, they are going to continue to be different, year is not independent of the prior year.

You need a baseline measure for both groups, then plot their GPA across time with 95% confidence interval to visualize the time series.

Something like the following. Also, I don't see any harm in using the full B sample, unless a priori you said you were going to use the subsample. A greater sample size will equal smaller standard errors. Just report that you ran it both ways, and the full sample was the post hoc test.

http://www.jimmunol.org/content/jimmunol/196/12/5047/F9.large.jpg?width=800&height=600&carousel=1

EDIT: Even the attrition rate is very similar, with 2015 numbers at 79% of 2012 for A, and 77% of 2012 for B I think this study shows that other factors play greater influence than the characteristics looked at here.

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Quite a few rigors are needed to accurately model these data. However, I think a big question is what will these data be used for. If the results will actually impact decisions, you need to make sure you adhere to best practices. If the results are for a class homework, well you may be able to settle for less than perfect.

P.S., It is a little surprising all of your random samples are bigger than the mean.

Quite a few rigors are needed to accurately model these data. However, I think a big question is what will these data be used for. If the results will actually impact decisions, you need to make sure you adhere to best practices. If the results are for a class homework, well you may be able to settle for less than perfect.

P.S., It is a little surprising all of your random samples are bigger than the mean.

This data is part of a dissertation-- I hope to have the draft writing done today. I have a lot to talk about in my limitations section! back to work...

1) do the t-test for for the difference of the GPA scores for each of the years. (What rogojel did above.) Then the standard error will be known (or at least estimated) and thus the variances of these differences.

2) what is the sum of these differences over the 4 years? And what is the variance of that sum? (The variance of the sum is the sum of the variances. (I assume that they can be assumed to have zero correlation.)

3) What is the mean of that sum (divide it by 4) and what is the variance of that overall mean. Then you will have the t-test for the overall mean.

A little bit interesting is that I have no intuition if this will be significant or not. Although I have some experience as a statistician.

Show us the result!