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Trend tests in epidemiology : P-values or confidence intervals?
| Content Provider | Semantic Scholar |
|---|---|
| Author | Hothorn, Ludwig A. |
| Copyright Year | 1999 |
| Abstract | Frequently, p-values are used in reporting epidemiological trend data. Because a p-value is a confounded mixture of effect size and sample size in dichotomous data, Lang, Rothman, and Cann (1998) recommended the slope of a trend line with its standard error and a graphical presentation containing the rate ratios as a function of mid-exposure levels. However, the slope contains the assumption of a dose-response function. This article discusses a proposal based on odds ratios and the corresponding one-sided lower confidence intervals for pair-wise comparisons (‘exposure levels with zero exposure’) as well as comparisons between incremental exposure levels. The proposed method allows both decisions on the global trend, the lowest-observed-adverse-effect-level (LOAEL) and the non-observed-adverse-effect-level (NOAEL), and a simple exploratory analysis. |
| Starting Page | 817 |
| Ending Page | 825 |
| Page Count | 9 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www2.fiu.edu/~kibriag/stat6244/Project/Pvalue.pdf |
| Alternate Webpage(s) | https://doi.org/10.1002/%28SICI%291521-4036%28199911%2941%3A7%3C817%3A%3AAID-BIMJ817%3E3.0.CO%3B2-C |
| Volume Number | 41 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
