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post hoc tests you can ask for more more
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comparisons here but not in a one way I
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know but you have to have between I
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believe you have to have a between
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subjects effect to actually get these
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and when you combine the repeated
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measures and between subjects effect in
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the same ANOVA you're talking about a
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split plot ANOVA or what some people
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unfortunately call a mixed design and
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OVA which is confusing because sometimes
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people confuse it with a mixed effects
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ANOVA which is actually a totally
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different analysis so those are the the
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main things I'm going to choose for this
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basic one-way repeated measures ANOVA
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and I'm going to click OK to run the
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analysis so SPSS is going to give me the
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first box here which is this first box
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here is a warning and it's just telling
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me that it couldn't do one of the
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homogeneity of variance tests which is
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the Levine's test of homogeneity of
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variance in fact you know I'm not even
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too sure if I had to click that
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homogeneity button because I know it
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might actually give the test that I'm
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going to take a look at in a second just
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automatically so within subjects table
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here is just telling me what my my
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factor looks like it's got three levels
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time one time two times three so people
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took the same IQ test three times in a
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row let's just say a month apart and we
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can see the means and the standard
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deviation see and we can see the mean is
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increasing linearly so time one to time
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two an increase of about one point three
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five a one point one point in the means
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and then it goes up again by about about
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one and we can see the standard
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deviations here and we can also see that
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the standard deviations are increasing
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across and usually in repeated measures
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designs in the real world the standard
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deviation does increase over time people
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at the last time period will usually
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have the largest standard deviation and
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it's larger usually sometimes
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substantially larger than the time one
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and one of the assumptions of the
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repeated measures ANOVA is that there is
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homogeneity of variance and it tests it
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with a test called much less Tessa's
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veracity which I'm going to get to in a
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minute this is the multivariate
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estimates and it's outputted by SPSS
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automatically it is a legitimate
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analysis that something people often do
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it
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PETA measures design and I'm going to
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follow that up in a future video I'm
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going to talk about repeated measures
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and over in the multivariate manova
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context but i'm not going to talk about
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it in this analysis except to say when
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you violate the assumption of modulus
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tests for its diversity some people
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often go to the multivariate test
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because it doesn't assume that what is
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much least tessa sphericity is something
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that typically you do not want to reject
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the null hypothesis for marshalese test
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of sphericity is indirectly testing the
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assumption that your variances or
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standard deviations are actually going
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to be the same as well as the
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covariances between time 1 time 2 and
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time 3 now typically I'm going to talk a
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little bit more about this right now to
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get an understanding what's going on
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unfortunately spss doesn't give you the
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correlation between time 1 time 2 and
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times 3 so people who scored high at
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time 1 on this IQ test most likely also
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scored high at time 2 and also most
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likely scored time scored high at time 3
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so there's a correlation between the
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dependent variable scores from time one
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time to two times three the repeated
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measures ANOVA assumes that that
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correlation between time one and time
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two and between time 1 and time three
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and between time to and times three is
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going to be equal so let's actually take
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a look at this let's look at the
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correlation so we get the correlations
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between time 1 time 2 and time 3 and we
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can see that there is some deviations
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time 1 the time two are about the same 8
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point 8 5 in time 2 and time three point
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eight between time - and times 3 and
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then time one time 0.85 roughly the same
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but then only 0.65 between time 1 and
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time 3 so the correlation is actually
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going down as we get further and further
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away from time 1 which is what usually
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you see in practice and much less esses
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erisa t indirectly tests that these
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correlations are the same
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I won't go into too much detail about
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exactly what monsters Texas versity is
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testing except to say that it's not
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actually testing directly that the
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variances and covariances or
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correlations are the same you can get a
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variance covariance matrix in SPSS by
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going into the reliability analysis
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utility and click on statistics and
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getting covariances here interitum will
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present pretend that our variables are
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items they're not the dist variables but
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we can get the variance covariance
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matrix and what repeated measures ANOVA
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assumes is that these variances here
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time one's variance is 7.85 that's
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simply this
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