5
votes
how to calculate R-squared in glm?
Zheng, B. and A. Agresti. 2000.
Summarizing the predictive power of a generalized linear model. Statistics in Medicine 19: 1771–1781 gave guarded recommendation of the square of the correlation ...
- 53.9k
4
votes
SAS fails to fit a mixed model
The SAS model you have fitted is not the same as the one you fitted with lme4::lmer. You have specified an unstructured variance-covariance matrix for the residual ...
- 56.5k
3
votes
Manually compute ARIMAX forecast
Your manual computation computes an ARIMAX forecast. Unfortunately, that is not what arima() models. Rather, arima() models and ...
- 117k
3
votes
Calculating minimum sample size required for repeated measures linear mixed model using the simr package
Some Background
Since you don't have a strong idea yet of what effects to expect, I recommend that you try to find articles that cover this to a degree. There is a lot of reaction time studies out ...
- 8,250
3
votes
A good fit of the model but the estimates are very low
It seems that the low numeric values of the coefficient estimates from your model are your primary concern. That's not a problem on its own, as the numeric values of those estimates depend on the ...
- 86.5k
2
votes
Root-finding via Robbins-Monro method: A real and simple example
To add to @whuber's excellent answer, and to further address OP's question "How to make the RM perform better?", the condition presented where b=0.25 or ...
- 2,906
2
votes
Alternative test instead of logistic regression for binary dependent outcome variables?
This is absolutely the solution to the problem. The logistic regression is setup specifically to predict the probability of an event happening, which can only have two possibilities in the binary case,...
- 8,250
1
vote
Accepted
Using 95% confidence intervals for pairwise comparisons in mixed effects model
The point estimates and standard errors agree perfectly between the two methods, and the confidence limits calculated the two ways are very similar (probably due to the difference between z- based and ...
- 86.5k
1
vote
Extreme values affecting mean in regression analysis
Welcome to CV. Yes, both analyses could be affected by extreme scores. What to do about it depends on details, but here are some thoughts.
I am not usually a fan of transforming data, but here, I ...
- 109k
1
vote
2-way Anova on Unequal Group Proportions
Which method or technique should I use to account for the binary response variable?
For a binary response you can use logistic regression. In SAS that would be ...
- 56.5k
1
vote
Visualising complex data with various groups + sub-groups over time period
Your visualization duplicates the "salesman" rows, which worsens the problem relative to adding more salespeople. In addition, if you use color to show quantity, absence of data could be ...
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1
vote
Alternative test instead of logistic regression for binary dependent outcome variables?
Certainly, that is indeed the correct statistical approach, as it involves a binary outcome variable (complications: yes/no) predicted by your predictors (e.g., age, gender). To obtain the probability ...
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