Displaying 4 results from an estimated 4 matches for "ranktest".
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randtest
2017 Jun 26
2
Classic fail-safe N
...sf.ies=escalc(xi=cases,ni=total,measure="PLO",data=dat) #I transform
the data using the logit transformation first. In CMA, it also uses the
logit transformation.
transf.pes=rma(yi,vi,data=transf.ies,method="DL",weighted=TRUE) #Pooling
individual effect sizes in the logit scale.
ranktest(transf.pes) #Performing the fail-safe N.
*Below are the results from R:*
Fail-safe N Calculation Using the Rosenthal Approach
Observed Significance Level: <.0001
Target Significance Level: 0.05
Fail-safe N: 8446
*Below are the Classic fail-safe N results from CMA:*
Z-value for observed studi...
2017 Jun 26
0
Classic fail-safe N
...es,ni=total,measure="PLO",data=dat) #I transform
>the data using the logit transformation first. In CMA, it also uses the
>logit transformation.
>transf.pes=rma(yi,vi,data=transf.ies,method="DL",weighted=TRUE) #Pooling
>individual effect sizes in the logit scale.
>ranktest(transf.pes) #Performing the fail-safe N.
>
>*Below are the results from R:*
>Fail-safe N Calculation Using the Rosenthal Approach
>Observed Significance Level: <.0001
>Target Significance Level: 0.05
>Fail-safe N: 8446
>
>*Below are the Classic fail-safe N results from...
2017 Jun 25
0
Classic fail-safe N
...sf.ies=escalc(xi=cases,ni=total,measure="PLO",data=dat) #I transform
the data using the logit transformation first. In CMA, it also uses the
logit transformation.
transf.pes=rma(yi,vi,data=transf.ies,method="DL",weighted=TRUE) #Pooling
individual effect sizes in the logit scale.
ranktest(transf.pes) #Performing the fail-safe N.
*Below are the results from R:*
Fail-safe N Calculation Using the Rosenthal Approach
Observed Significance Level: <.0001
Target Significance Level: 0.05
Fail-safe N: 8446
*Below are the Classic fail-safe N results from CMA:*
Z-value for observed studi...
2012 Apr 19
2
ANOVA in quantreg - faulty test for 'nesting'?
I am trying to implement an ANOVA on a pair of quantile regression models in
R. The anova.rq() function performs a basic check to see whether the models
are nested, but I think this check is failing in my case. I think my models
are nested despite the anova.rqlist() function saying otherwise. Here is an
example where the GLM ANOVA regards the models as nested, but the quantile
regression ANOVA