How to embed Cyberball Game into E-prime program?

I am conducting a meta-analysis between 2 variables. Both variables are different types of taste. For eg stimulus 1 is sweet and stimulus 2 is bitter and I note the correlation between these two taste modalities. In some scientific papers the correlation between these stimulus 1 and stimulus 2 as given as pearson r and in some studies it's given as spearman correlation coeff. So can I use these 2 different types of effect size in the same meta-analysis? Is there a way to transform these 2 different types of effect sizes into a common effect size? Or do I have to conduct the meta-analysis separately for individual effect size?

Thank you for your attention

Hi All,

I am testing a series of CFA models (single factor, correlated traits factor, higher-order factor and bifactor model) using AMOS. This test was conducted to validate a translated questionnaire.

There are three items that should be reverse scored. However, whenever I insert the reversed items in any models, Amos output always showed 'iteration limit reached...' and the standardized factor loadings cannot be retrieved. When I used the original items (without reversing score), the Amos showed positive output which is 'minimum was achieved'.

My question is:

1) Are the items actually not representing the measurement scale?

2) Can we still report the model fit indices from the output that says 'iteration limit reached'? even some models showed acceptable fit?

2) If I decided to use the original items (without reversing the scores) because the Amos can provide the output 'minimum was achieved' (regardless the outcome of fit indices), am I doing it correctly? I decide to interpreted it as the need to use the original items in the future studies.

I attached the pictures of a single factor model with original items and reversed score items. Hope someone can enlighten me, thanks so much for the help!

While analyzing meta-analysis of RCTs, can we pool together the effect measures of studies that performed ITT and PPA?

Here. I am estimating the effect measures de novo from the sample size (baseline/endline), mean and s.d. of each study in Stata 17.0. While selecting the sample size, I have the option to either select baseline or endline for all the studies. So, is it right to select endline for all the studies, while a few studies provide mean based on ITT, and vice versa. I did not find it right, epidemiologically?

If so, what are the other ways of doing it?

- Can I estimate effect measures for individual studies based on ITT/PPA and use the pre-computed option to get a pooled estimate?

- Or can I do a sub-group analysis?

Thank you

I need to calculate Fail-Safe N of my meta-analysed studies. I am having difficulty in understanding Orwin's method. Can anyone please elaborate with the help of an example?

Hi,

I am currently trying to undertake a meta-analysis that looks at the difference between community-dwelling adults and those residing in various care settings.

Originally I had planned to calculate standardised mean differences (SMD) as the studies I found in my initial search presented the means and standards deviations of the community-dwelling and 'instititutionalised' adults. Unfortunately, this is obvious not the norm as the majority of the studies I have now found (which provide relevant and needed information) solely present the mean and standard deviation for one 'institutionalised' population. From this I have been able to calculate the 95% confidence intervals for each study and have put them into a forest plot to see how homegenous they are.

However I do not know if this is a valid type of meta-analysis, if it is - what is it called? Everytime I find something about meta-analysis of means its about SMD. If it isn't a valid form of meta-analysis is there another method that I could use? Or is there a way to impute a community-dwelling mean for the studies that don't present one so that I can use SMD's?

Many thanks,

Lucy

I am conducting a meta-analysis on correlations among some constructs. So far based on what I have read from meta-analysis resource books and the literature, usually we first transform Pearson r to Fisher's z for meta-analysis, and then transform Fisher's z back to Pearson r for final report. Then I got the following basic questions.

1) Is only Pearson r be included in meta-analysis? What about other types of correlations, such as Spearmen rho, point biserial correlation, etc?

2) Refer to the Comprehensive Meta-analysis, it said t-value can be used to convert to correlation r. Which sort of t-value does it refer to? Is it the t-values in multiple regressions results tables, which can be converted to partial correlation coefficient? What about t-value from independent samples t-test, say, on mental wellbeing between male and female?

3) Any well-defined set of quality assessment tool and framework for correlational studies?? like the Cochrane Risk of Bias Tool for randomized controlled trials?

4) I got 4 coders to code the included studies. Generally speaking, how to calculate the inter-coder reliability of their codings?

Any advices and resources would be appreciated. Thanks all.

Is it possible to transform a bimodal variable into normal or other 'more friendly' distribution variables? If not, what statistical analysis can be done for a bimodal dependent variable to include spatial correlation? Are Generelized Estimating Equations fit for this purpose?

I'm using the Taylor Aggression Paradigm in my research at the moment and it requires a simple competitive reaction time task in which participants indicate when a stimulus in the centre of the screen changes colour (e.g. a blue square become red), and are given immediate feedback on their performance.

The nature of the stimulus isn't really important, as long as some sort of obvious change occurs.

I was planning to create this task using E-Prime (which I'm entirely new to), but does anyone have a similar task already set up that I could maybe 'recycle'? Or if not, any tips for setting one up in E-Prime?