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8h
revised Ambiguity of chi-squared test of association; how can the conclusion change using the ''same'' sample?
edited for English; formatted
8h
reviewed Reviewed Creating a mixed model for repeated measure using lme function
8h
revised Creating a mixed model for repeated measure using lme function
shortened title; added tags; formatted; removed extra comments; light editing
9h
revised aggregate all data by Date and ID
light editing
9h
reviewed No Action Needed aggregate all data by Date and ID
9h
reviewed Reviewed media classification open-source software
9h
comment Correlation between OLS estimators for intercept and slope
Related: Why does the standard error of the intercept increase the further $\bar x$ is from 0?
10h
reviewed Close When to stop agglomerative hierarchical clustering - stopping criteria
10h
comment When to stop agglomerative hierarchical clustering - stopping criteria
As written this is hard to follow. My guess is that what you are asking is too broad to be answerable here. Probably what you need is to take a complete course on clustering, not a few paragraphs. That said, this may help you: Where to cut a dendrogram?
11h
reviewed Reviewed How to conduct a three way ANOVA with non-normal and heteroscedastic data?
11h
comment How to conduct a three way ANOVA with non-normal and heteroscedastic data?
In what way were the data non-normal? Were the residuals non-normal, or all the Y values together? How far from normality were they? What is the "root square" transformation & how does it differ from the square root transformation?
11h
revised How to conduct a three way ANOVA with non-normal and heteroscedastic data?
shortened title; edited tags; removed extra comments; edited
11h
comment How to conduct a three way ANOVA with non-normal and heteroscedastic data?
It might help to read my answer here: Alternatives to one-way ANOVA for heteroskedastic data.
12h
reviewed Reviewed Quantile Regression: follow up methods to have a more fine-grained understanding of what the results really mean?
12h
revised Quantile Regression: follow up methods to have a more fine-grained understanding of what the results really mean?
removed extra comments
12h
reviewed Reviewed Decision Trees rpart R categorical and continuous variables
12h
comment Decision Trees rpart R categorical and continuous variables
Could it be that the categorical variables aren't relevant once you've accounted for the continuous variables?
13h
reviewed Close Determining PCA scores for a new data point
15h
reviewed Close BIC in two step clustering
15h
reviewed Close Power and sample size