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| bio | website | |
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| location | ||
| age | ||
| visits | member for | 1 year |
| seen | Apr 5 at 13:10 | |
| stats | profile views | 10 |
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Dec 18 |
comment |
Factor scale as a dependent variable in repeated measures ANOVA Tank you for your answer, ThomasH. I leave the question open just to see if anyone can address the rest of the question. |
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Sep 13 |
asked | Factor scale as a dependent variable in repeated measures ANOVA |
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Jun 26 |
asked | What is the difference between corAR1 and corCAR1 correlation structures? |
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Jun 22 |
awarded | Tumbleweed |
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Jun 15 |
asked | How to check and correct heteroskedasticity in a multilevel model? |
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Jun 12 |
comment |
Multilevel covariance structure and more Thank you gung and @Seth for your answers (+1 to each). I've fitted a model without time slopes and AR1 covariance structure, and plotted the residuals as (I've interpreted that) Seth indicates: a spaguetti plot in which x axis is time, y axis is the residual values, and a colour for each subject. The graphic shows all the lines starting together and spreading up and down as time passes. Is this correct? Regarding this residuals distribution, should I use the AR1 covariance structure? |
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Jun 8 |
comment |
Multilevel covariance structure and more Seth, thank you for your explanation, but I don't understand some aspects of it (it's my fault, I'm a beginner in statistic). I think that my data are heteroskedastic because I plotted the measurements of all subjects in each trial and visually it seems that the variance is very different between trials. Maybe it's not a correct way to do it. How can I check the within subjects homokesdasticity of my data? |
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Jun 8 |
comment |
Multilevel covariance structure and more On the other hand, there is an evident correlation between pairs of obervations, that decreases as time gets further apart. So I think my data are not completely unestructured. Is there any variance-covariance structure that accounts for this different variance at each time, but with correlations between the closer measures? Thank you! |
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Jun 8 |
comment |
Multilevel covariance structure and more Thank you @gui11aume and gung for your very useful answers (+1 to each). Concerning to the inclusion of TIME in the model, I understand and agree with your argumentations: it have to be in the model. I've tried to include it both as fixed and random factor, and the model is improved (-2LogLik comparison), although CONDITION is not a significant predictor. But I still keep doubts about the variance-covariance structure: I think my data are heterokedastic (unequal variances), so I should not specify AR1. But when I do it the model fits better. Is it a proof of anything? (continue) |
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Jun 7 |
awarded | Supporter |
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Jun 7 |
awarded | Editor |
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Jun 7 |
revised |
Multilevel covariance structure and more added 4 characters in body |
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Jun 6 |
asked | Multilevel covariance structure and more |
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Jun 5 |
comment |
Data standardization in a repeated measures multilevel model Thank you, StasK, for your answer (I'm a newcomer and don't have enough reputation to mark your response as useful, otherwise I would). I've seen many papers using this kind of standardized scores in statistical analysis in my field, but not with multilevel models. So I think I'll follow your advice... Thank you! |
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Jun 2 |
awarded | Scholar |
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Jun 2 |
accepted | Data standardization in a repeated measures multilevel model |
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Jun 2 |
comment |
Fixed effects contrasts in multilevel model Thank you, Macro and MichaelChernick, for your comments. I didn't find it that harsh; I'm sure I should have checked better the previous posts related to my question. It's just I'm new in statistics and not sure I'm understanding well some concepts... Do you think it is correct if I interpret that the independent variable is not significant as predictor, but there is a significant difference in the de dependent variable values related to the independent variable? Is it possible? |
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Jun 1 |
asked | Fixed effects contrasts in multilevel model |
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May 30 |
comment |
Data standardization in a repeated measures multilevel model Ok, I understand... I'll check Jeff Rouder site. But, just to be curious, do you think the kind of standardizarion that I have done is incompatible with a multilevel model per se; o just in this particular case (RT data)? Imagine that, with other kind of data (e.g. psychophysiological) after the standardization we obtain a normal distribution; do you think that, in that case, there would be any problem to fit a multuilevel model? Thank you for your answer! |
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May 29 |
asked | Data standardization in a repeated measures multilevel model |
