Comments (5)
Hmm, good point. I'm inclined to agree that option 1 is preferable, but I would want to be sure that the stat is documented in the print method.
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Looking at calculate()
right now, I think it'll make sense to abstract it a bit: create really only two if/thens - one for the single stat and one for the grouped stat (differences in props/means). This will make the code more concise, but also make it easier to extend for a generic FUN. I'll wait on that until Chisq and F are done to be sure that re-factoring makes sense.
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Option 1 sounds great! The note will be helpful too.
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This comment
Looking at calculate() right now, I think it'll make sense to abstract it a bit: create really only two if/thens - one for the single stat and one for the grouped stat (differences in props/means). This will make the code more concise, but also make it easier to extend for a generic FUN. I'll wait on that until Chisq and F are done to be sure that re-factoring makes sense.
seems to be in the wrong issue. I'd suggest opening a separate issue about this.
More importantly, isn't this the job of the stat function, not of calculate()
? The fact that you have to extend things to work with a general function makes me worry that you are building a system that isn't really open at its core and will need a redesign after your initial experimentation.
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This issue has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue.
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Related Issues (20)
- improve argument checking
- add / polish alt text HOT 1
- infer::observe() conflicts with shiny::observe() HOT 2
- Clarify whether chisq_test is supposed to give same results as base::chisq.test() HOT 2
- Hex logo missing on package homepage HOT 9
- t where it should be p-value in the documentation HOT 2
- How about add a function to run all workflow? HOT 2
- Error in quantile.default(x[[ncol(x)]], probs = (1 + c(-level, level))/2) : missing values and NaN's not allowed if 'na.rm' is FALSE HOT 3
- t-test bootstrapped p-values very different compared to permutation HOT 4
- Null Distribution of SD not Appropriately Calculated HOT 3
- fill = NULL argument not working for shade_ci() HOT 2
- rep_slice_sample on groups with multiple n values HOT 2
- Warnings about aesthetic length and no non-missing argument to min in visualise + shade_p_value functions HOT 5
- snap changes with additional warning context on R-devel HOT 4
- messages on `devtools::document()` HOT 2
- reduce noise in `devtools::test()` HOT 1
- Release infer 1.0.7 HOT 1
- rep_slice_sample unused argument error in vctrs:vec_chop HOT 4
- Change default of permuted p-values according to literature to avoid p-values being 0 HOT 2
- Allow visualize() to give density curve on non theoretical distribution HOT 3
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