best test for this analyses?
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I would be greatful for advice on analysing this data in SPSS
A study was done of comparing test results (% correct responses) on two subjects biology and english. The tests are supposedly adjusted so as to be of equal difficulty (approx). The study was done in 3 years of a school at the same time. So we have 33 subjects in year 1 tested on biology and english (the same participants were tested twice, once in each subject - i.e. repeated measures) from year 1, same for year 2, same for year 3 (total 99 participants) SO the research question is whether there are differences on the basis of subject (i.e. do scores on biology differ significantly from those on english) and whether performance improves over the years (i.e. is year 2 better than year 1, is year 3 better than year 2). I was thinking ANOVA with multiple comparison tests. Problem is that normality tests show not normal distribution (KS And SW) so then thinking kruskall wallis but the assumption of the variables having the same shaped distribution is not met (one has a positive skew the other negative). I ran the kruskall wallis test anyway and it showed significant differences by year for one of the subjects (english)but not for the other (biology). Even of I could use KW this still leaves the issue of how to do multiple comparison test with non parametric data, to find out which years differ from which. Reading suggests this is obscure process with non parametric data? Then there is the other research question - hoe to test for significant differences on basis of subject? Think I need to give this more thought bit any guidance much appreciated Thanks ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
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Ps just to say that I think I can use wilcoxon for testing whether
performance differs significantly between biology and english and I guess I can do that per year or all years combined. --- I would be greatful for advice on analysing this data in SPSS A study was done of comparing test results (% correct responses) on two subjects biology and english. The tests are supposedly adjusted so as to be of equal difficulty (approx). The study was done in 3 years of a school at the same time. So we have 33 subjects in year 1 tested on biology and english (the same participants were tested twice, once in each subject - i.e. repeated measures) from year 1, same for year 2, same for year 3 (total 99 participants) SO the research question is whether there are differences on the basis of subject (i.e. do scores on biology differ significantly from those on english) and whether performance improves over the years (i.e. is year 2 better than year 1, is year 3 better than year 2). I was thinking ANOVA with multiple comparison tests. Problem is that normality tests show not normal distribution (KS And SW) so then thinking kruskall wallis but the assumption of the variables having the same shaped distribution is not met (one has a positive skew the other negative). I ran the kruskall wallis test anyway and it showed significant differences by year for one of the subjects (english)but not for the other (biology). Even of I could use KW this still leaves the issue of how to do multiple comparison test with non parametric data, to find out which years differ from which. Reading suggests this is obscure process with non parametric data? Then there is the other research question - hoe to test for significant differences on basis of subject? Think I need to give this more thought bit any guidance much appreciated Thanks ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
Re: best test for this analyses?
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In reply to this post by researcher
Theory suggest you can use a KW test and Mann-Whitney test for multiple comparisons (A vs. B; B vs. C; A vs. C). You must apply the Bonferroni correction (alpha/number of groups to be compared) in order to adjust the post-hoc p-value. This is a quick and dirty explanation, maybe the moguls here can shed a little more info in this matter.
Hope this helps, Gerónimo Maldonado-Martínez, statistician in constant search of light |
Re: best test for this analyses?
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In reply to this post by researcher
I know you've gotten a reply already but I don't completely understand the dataset. Two different tests, 33 people take each test in year 1. Do the same 33 people take each test in years 2 and 3? OR, like in a school, is it three groups of 33. Makes a big difference in the analysis. How much non-normality is there? What are the skew and kurtosis numbers?
Gene Maguin -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of M Sent: Saturday, March 15, 2014 10:15 AM To: [hidden email] Subject: best test for this analyses? I would be greatful for advice on analysing this data in SPSS A study was done of comparing test results (% correct responses) on two subjects biology and english. The tests are supposedly adjusted so as to be of equal difficulty (approx). The study was done in 3 years of a school at the same time. So we have 33 subjects in year 1 tested on biology and english (the same participants were tested twice, once in each subject - i.e. repeated measures) from year 1, same for year 2, same for year 3 (total 99 participants) SO the research question is whether there are differences on the basis of subject (i.e. do scores on biology differ significantly from those on english) and whether performance improves over the years (i.e. is year 2 better than year 1, is year 3 better than year 2). I was thinking ANOVA with multiple comparison tests. Problem is that normality tests show not normal distribution (KS And SW) so then thinking kruskall wallis but the assumption of the variables having the same shaped distribution is not met (one has a positive skew the other negative). I ran the kruskall wallis test anyway and it showed significant differences by year for one of the subjects (english)but not for the other (biology). Even of I could use KW this still leaves the issue of how to do multiple comparison test with non parametric data, to find out which years differ from which. Reading suggests this is obscure process with non parametric data? Then there is the other research question - hoe to test for significant differences on basis of subject? Think I need to give this more thought bit any guidance much appreciated Thanks ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
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the OP may also want to
consider the IDF.* function since the equivalence of the two
topics -- English and bio -- may be questioned.
Art Kendall Social Research ConsultantsOn 3/19/2014 11:20 AM, Maguin, Eugene [via SPSSX Discussion] wrote: I know you've gotten a reply already but I don't completely understand the dataset. Two different tests, 33 people take each test in year 1. Do the same 33 people take each test in years 2 and 3? OR, like in a school, is it three groups of 33. Makes a big difference in the analysis. How much non-normality is there? What are the skew and kurtosis numbers?
Art Kendall
Social Research Consultants |
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In reply to this post by researcher
"99 participants" says that there are 3 sets of 33.
First: Do you need to abandon ordinary ANOVA? Bruce Weaver provided the proper quotation after I botched the reference a few years ago - The version of that quote I know is another George Box classic. "To make the preliminary test on variances is rather like putting to sea in a rowing boat to find out whether conditions are sufficiently calm for an ocean liner to leave port!" Box G. E. P. (1953) Non-normality and tests on variances. Biometrika 40, 318�35. " Second: The weaker assumption for a paired t-test, which would test whether 99 scorers are higher on biology than English, is that the *difference* is normal. If you set the design up as ANOVA, the assumption is that the residuals are normal. If you actually do have opposite skew in the two tests... that seems to be a rather unfortunate indication that, whatever assurances you may have received, the "matching" of the tests was done "by sample", not by scoring at different levels; and (I'm pretty sure) the match would be reliable only for the particular level of skill of the matching sample. I, therefore, might want to decide that the two scales are not parallel enough to analyze together, except for by overall level. After the paired-t comparison, I would look at the separate linear trends for English and bio. -- Rich Ulrich > Date: Sat, 15 Mar 2014 10:14:58 -0400 > From: [hidden email] > Subject: best test for this analyses? > To: [hidden email] > > I would be greatful for advice on analysing this data in SPSS > > A study was done of comparing test results (% correct responses) on two > subjects biology and english. The tests are supposedly adjusted so as to be > of equal difficulty (approx). > > The study was done in 3 years of a school at the same time. > > So we have 33 subjects in year 1 tested on biology and english (the same > participants were tested twice, once in each subject - i.e. repeated > measures) from year 1, same for year 2, same for year 3 (total 99 > participants) > > SO the research question is whether there are differences on the basis of > subject (i.e. do scores on biology differ significantly from those on > english) and whether performance improves over the years (i.e. is year 2 > better than year 1, is year 3 better than year 2). > > > I was thinking ANOVA with multiple comparison tests. Problem is that > normality tests show not normal distribution (KS And SW) > > so then thinking kruskall wallis but the assumption of the variables having > the same shaped distribution is not met (one has a positive skew the other > negative). > > I ran the kruskall wallis test anyway and it showed significant differences > by year for one of the subjects (english)but not for the other (biology). > > Even of I could use KW this still leaves the issue of how to do multiple > comparison test with non parametric data, to find out which years differ > from which. Reading suggests this is obscure process with non parametric > data? > > Then there is the other research question - hoe to test for significant > differences on basis of subject? > > Think I need to give this more thought bit any guidance much appreciated > |
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