search for: geisser

I'm an experimental psychologist and when I run ANOVA analysis in SPSS, I normally ask for a test of non-sphericity (Box's M-test). I also ask for output of the corrections for non-sphericity, such as Greenhouse-Geisser and Huhn-Feldt. These tests and correction factors are commonly used in the journals for experimental and other psychology reports. I have been switching from SPSS to R for over a year now, but I realize now that I don't have the non-sphericity test and correction factors. The backgroud to t...

Hi all, I was wondering whether there are any packages that provide for the Greenhouse-Geisser correction, an adjustment used in univariate repeated measures when the sphericity assumption is violated (both numerator and denominator degrees of freedom are multiplied by GG-epsilon, and the significance of the F ratio is evaluated with the new degrees of freedom)? I have seen a few emails...

...2, and 7 levels. or with an additional fourth between subjects factor D. Everything works fine using aov(val ~ A*B*C + Error(subject/ (A*B*C) ) ) or aov(val ~ (D*A*B*C) + Error(subject/(A*B*C)) + D ) val, A, B, C, D and subject are columns in a data.frame. How can I get the estimated Greenhouse-Geisser and Huynh-Feldt epsilons? I know Peter Dalgaard described it in R-News Vol. 7/2, October 2007. However, unfortunately I am not able to apply that using my data... Furthermore, I am still confused of how SPSS calculates the epsilons since it is mentioned that perhaps there are any errors in SPSS?...

Hi, I've looked in the mailing list archives and found some questions related to Greenhouse-Geisser epsilon correction. Are there any packages providing that? Thanks, Sven -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe"...

...cies ~ congr*isi + Error(subj/(congr*isi)),data=dats) "congr" has 4 levels, while "isi" has "3" levels. I would like to check for possible violations of the sphericity assumption, and following the example given by Baron and Li(2004), I was able to compute Greenhouse-Geisser epsilon for the effect of "congr" and for the effect of "isi". I calculated the variance/covariance matrix for each of these terms by averaging the "latencies" across the levels of the other factor, but I can't figure out how to calculate the variance/covariance m...

...n R and how to compute corrected df for the F-test if the assumption is violated. Back when I taught this course using SPSS it was relatively straightforward - we would look at Mauchly's test of sphericity - if it was significant, then we would use one of the corrected F-tests (e.g. Greenhouse-Geisser or Huynh-Feldt) that were spat out automagically by SPSS. I gather from searching the r-help archives, searching google, and searching through various books on R, that the only way of using mauchly.test() in R is on a multivariate model object (e.g. mauchly.test cannot handle an aov() object). Qu...

...2.4321176 > > Adj Pr > F > Source G - G H - F > > roi <.0001 <.0001 > Error(roi) > > > Greenhouse-Geisser Epsilon 0.5367 > Huynh-Feldt Epsilon 0.6333 > > > Source DF Type III SS Mean Square F Value Pr > F > > ord 1 2.2104107 2.2104107 0.24 0.6276 > Error(ord) 19 17...

...for the topics of random factors in ANOVA, repeated measures in ANOVA, or within subjects designs in R. Could anyone point us to any information concerning - univariate approach to repeated measures anova - multivariate approach to repeated measures anova - mixed designs - Greenhouse-Geisser epsilon correction - Newman-Keuls contrasts - LSR contrasts - Tukey contrasts - Scheffe contrasts Any help or comment appreciated. Since we are not in the mailing list yet, please cc your reply to volker.franz at tuebingen.mpg.de. Thanks, Volker -- _________________________________...

...it0 <- lm(data.n ~ 0 + SGROUP) > mlmfit1 <- lm(data.n ~ 1 + SGROUP) > anova(mlmfit1,mlmfit0,test="Spherical",M=~hemi,X=~1) Analysis of Variance Table Model 1: data.n ~ 1 + SGROUP Model 2: data.n ~ 0 + SGROUP Contrasts orthogonal to ~1 Contrasts spanned by ~hemi Greenhouse-Geisser epsilon: 0.6829 Huynh-Feldt epsilon: 0.7127 Res.Df Df Gen.var. F num Df den Df Pr(>F) G-G Pr H-F Pr 1 22 0.54295 2 22 0 0.54295 Inf 0 44 Warning messages: 1: NaNs produced in: pf(q, df1, df2, lower.tail, log.p) 2: NaNs produced in: pf(q, df1, df2, lower.tail, l...

...20.33 2 10.6667 12 11.438 0.001660 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Mauchly Tests for Sphericity Test statistic p-value fB 0.87891 0.7242 fattA:fB 0.87891 0.7242 Greenhouse-Geisser and Huynh-Feldt Corrections for Departure from Sphericity GG eps Pr(>F[GG]) fB 0.89199 0.0001474 *** fattA:fB 0.89199 0.0026452 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 HF eps Pr(>F[HF]) fB...

...) Fehler in L %*% B : nicht passende Argumente (Error in L %*% B : non matching arguments) On the other hand using anova.mlm I get > anova.mlm(lm(mat~1,data),idata=data.frame(zeit=factor(1:3)),X=~1,test="Spherical") Analysis of Variance Table Contrasts orthogonal to ~1 Greenhouse-Geisser epsilon: 0.7464 Huynh-Feldt epsilon: 0.7777 Df F num Df den Df Pr(>F) G-G Pr H-F Pr (Intercept) 1 11.767 2 58 5.1375e-05 3.1183e-04 2.4939e-04 Residuals 29 How can achieve this with Anova?...

...esently assuming no within-group correlation for the data, which I guess is unlikely in my example. Is there a way to compare directly (maybe in terms of log-likelihood?) similar models fitted in lme() and lmer()? 2. Baron & Li suggest a painful (at least for me) procedure to obtain Greenhouse-Geisser or Huyn-Feldt correction for the ANOVA analysis they propose. Is there a package or function which simplifies the procedure? 3. I must admit that I don't understand solution C. I can "hack" it to fit my model, and it seems to work, but I can't seem to grasp the overall concept, e...

...my.data, test="Spherical") Although this yields the result that, after correction, it's not significant - perhaps due to the low DF from this simple example -- Analysis of Variance Table Model 1: response ~ 1 Model 2: response ~ 1 - 1 Contrasts orthogonal to ~Treatment Greenhouse-Geisser epsilon: 0.3565 Huynh-Feldt epsilon: 0.4982 Res.Df Df Gen.var. F num Df den Df Pr(>F) G-G Pr H-F Pr 1 4 0.43167 2 5 1 0.50937 3.7939 4 16 0.02356 0.09620 0.06966 -- But, I still want to get my time and time*treatment interactions - what would be the...

...18 1.7786 0.1973 Region 748644 7 299408 63 22.5037 6.181e-15 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Mauchly Tests for Sphericity Test statistic p-value Shoe 0.72437 0.275329 Region 0.00032 0.006714 Greenhouse-Geisser and Huynh-Feldt Corrections for Departure from Sphericity GG eps Pr(>F[GG]) Shoe 0.78393 0.2065 Region 0.37482 8.391e-07 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 HF eps Pr(>F[HF]) Shoe 0.92023 0.2008 Region 0.54302...

...1 Error(roi) 95 231.0511739 2.4321176 Adj Pr > F Source G - G H - F roi <.0001 <.0001 Error(roi) Greenhouse-Geisser Epsilon 0.5367 Huynh-Feldt Epsilon 0.6333 and for the first one: Source DF Type III SS Mean Square F Value Pr > F ord 1 2.2104107 2.2104107 0.24 0.6276 Error(ord) 19 172.7047994...

Hi there, some statistical programs (e.g. SPSS) calculate a correction of the degrees of freedom in a repeated measure analysis of variance (see Greenhouse-Geisser (1958) or Huynh-Feld (1976)) by a factor epsilon. This factor is used to correct the deg. of freedom to get a corrected f-test. Is this also possible with R? Thanks, Sven P.S.: I read in the lm help page: singular.ok logical, defaulting to TRUE. FALSE is not yet implemented. but couldn'...

I have a between-subjects factor, A, with three levels, and a within-subjects factor with 4 levels. There are 6 subjects at each A level. I get the correct F tests using the aov function with the stack form of the data frame but I want the epsilon adjustment (Greenhouse-Geisser, Huynh-Feldt). for nonspheriicty as well. I got the SPSS results using the standard broad data frame (a row for each subject with two within-subject variables) in a simple repeated measures design but get an error message when one factor is between subjects.. I tried what I thought was a simpl...

...f. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > >Error: Within > Df Sum Sq Mean Sq F value Pr(>F) >Residuals 48 318 7 > This is mostly identical the analysis by BMDP 4V, except for the Greenhouse-Geisser epsilons, which are not estimated this way. I have to analyse a similar dataset, which is not balanced. So I need to change the method. Following Pinheiro/Bates p.90f, I tried > hf2.lme <- lme(ampl~gapf*bl,hframe2,random=list(VP=pdDiag(~gapf*bl),bl=pdDiag(~gapf))) and some variations of this...

...elatively small modifications of their lm counterparts. The actual test calculations need to be excised from summary.manova (generalize? e.g. mvlin.test(SSD1, SSD2, method="Pillai")). It should be possible to wedge in tests under sphericity assumptions (with Greenhouse-Geisser and Huynh-Feldt corrections), as well as transformation/conditioning matrices (see below). A more radical idea is to say that these are all different kinds of MANOVA tables and extend the *.manova functions to understand them. This would break the symmetry with lm, though, since y...

I have design with two repeated-measures factor, and no grouping factor. I can analyze the dataset successfully in other software, including my legacy DOS version BMDP, and R's 'aov' function. I would like to use 'Anova' in 'car' in order to obtain the sphericity tests and the H-F corrected p-values. I do not believe the data are truly deficient in rank. I