# Tag Info

93

There's a good reason for it. The value can be found via noquote(unlist(format(.Machine))) double.eps double.neg.eps double.xmin 2.220446e-16 1.110223e-16 2.225074e-308 double.xmax double.base double.digits 1.797693e+308 2 53 ...

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As they stand, neither one of Statement 1 or 2 is very useful. If 90% of passengers were women and 90% of people survived at random, then both statements would be true. The statements need to be considered in the context of the overall composition of the passengers. And the overall chance of surviving. Suppose we had as many men as women, 100 each. Here are ...

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What common practice is might depend on your field of research. The manual of the American Psychological Association (APA), which is one of the most often used citation styles, states (p. 139, 6th edition): Do not use any value smaller than p < 0.001

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I don't think the objection is to just the term "statistically significant" but to the abuse of the whole concept of statistical significance testing and to the misinterpretation of results that are (or are not) statistically significant. In particular, look at these six statements: P-values can indicate how incompatible the data are with a specified ...

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The point of providing descriptive statistics is to characterise your sample so that people in other centres or countries can assess whether your results generalise to their situation. So in your case tabulating the sex, grades and so on would be a beneficial addition to the logistic regression. It is not to enable people to check your assumptions although ...

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Significant digits are used in some fields (I learned about them in Chemistry) to indicate the degree of meaningful precision that exists in a number. This is an important topic in statistics as well, so in fact we report this constantly--we just report it in a different form. Specifically, we report confidence intervals, which indicate the level of ...

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There are several misunderstandings in you post (some of which are common and you may have been told the wrong thing because the person telling you was just passing on the misinformation). First is that bootstrap is not the savior of the small sample size. Bootstrap actually fairs quite poorly for small sample sizes, even when the population is normal. ...

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At its face, the conditional probability of surviving conditional on sex is more useful, simply because of the direction of information flow. A person's sex is known before her or his survival status, and this probability can be used in a predictive sense, prospectively. Also, it is not influenced by the prevalence of females. When in doubt, think ...

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Yes, non-significant results are just as important as significant ones. If you are reporting any result, always include the df, test statistic, and p value. And in that case, you should state the exact p-value, rather than generalising to >0.05

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According to this biology SE thread, the standard deviation of male adult height is about $0.07$ metres, and of females is about $0.06$ metres. Rounding these to one decimal place would give $0.1$ metres. The fact that the standard deviation is reported as $0.0$ metres indicates a standard deviation below $0.05$ metres ... but a standard deviation of, say, $... 15 Such extreme p-values occur more often in fields with very large amounts of data, such as genomics and process monitoring. In those cases, it's sometimes reported as -log10(p-value). See for example, this figure from Nature, where the p-values go down to 1e-26. -log10(p-value) is called "LogWorth" by statisticians I work with at JMP. 12 Wikipedia appears to have your answers. Here's an excerpt from the example statement of results: In reporting the results of a Mann–Whitney test, it is important to state: A measure of the central tendencies of the two groups (means or medians; since the Mann–Whitney is an ordinal test, medians are usually recommended) The value of U The ... 12 One reason for restricting the number of digits reported in many estimates, p-values, etc. is based on perception. Reporting something like p = 0.04872429 implies a level of precision in the results that causes them to be perceived as more accurate. Essentially, the use of high numbers of digits in reporting statistical results tastes too many of trying to ... 10 The Guide to Uncertainty in Measurement (GUM) recommends that the uncertainty be reported with no more than 2 digits and that the result be reported with the number of significant digits needed to make it consistent with the uncertainty. See Section 7.2.2 below http://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf The following code was my ... 10 In a log-linear model of an outcome$\ln y$with a continuous untransformed explanatory variable$x$and a dummy explanatory variable$d$:$100 \cdot \beta_x$is the percentage change in$y$for a small change in$x$(up or down) If d switches from 0 to 1, the percent change in$y$is$100 \cdot [\exp(\beta_d) - 1]$. If d switches from 1 to 0, the percent ... 10 I have not studied actual practice, so this reply cannot address that aspect of the question. As a general principle I would expect the treatment of significant digits in reporting the degrees of freedom (df) to be based on judgment related to significant figures. The principle is to be consistent: use the precision in one quantity that is appropriate for ... 10 This problem has come up in some of my research as well (as a epidemic modeler, I have the luxury of making my own data sets, and with large enough computers, they can be essentially arbitrarily sized. A few thoughts: In terms of reporting, I think you can report more precise confidence intervals, though the utility of this is legitimately a little ... 9 The beta regression model can have two submodels: (1) a regression model for the mean - similar to a linear regression model or a binary regression model; (2) a regression model for the precision parameter - similar to the inverse of a variance in a linear regression model or the dispersion in a GLM. So far you have just used regressors in (1) but just a ... 9 In my opinion one of more honest yet non-technical phrasing would be something like: The obtained result is surprising/unexpected (p = 0.03) under the assumption of no mean difference between the groups. Or, permitting the format, it could be expanded: The obtained difference of$\Delta m$would be quite surprising (p = 0.03) under the scenario of two ... 8 The problem with R is that there are so many ways to construct great reports, and so many R packages that are helpful for this task. One approach, though getting out of date, is shown in http://biostat.mc.vanderbilt.edu/wiki/pub/Main/StatReport/summary.pdf . Note that some of the functions there have been updated as shown in http://biostat.mc.vanderbilt.edu/... 8 I can't speak for the APA but I see value as a reader in having information on degrees of freedom and F statistics. Degrees of freedom provide reassurance about the scale of the study. The F statistic, as the ratio of explained variance to error variance, contains important information about how effective the model was. This cuts both ways. With a ... 7 You should report the significance (along with everything else) from the initial full model. As @Frank Harrell notes, stepwise model selection is invalid. (If you want to understand this more fully, it may help you to read my answer here.) People are often believe that leaving 'non-significant' variables in a model will cause it to be overfitted, but it ... 7 I don't think one needs a paper. The dependent variable is the Y variable (these are used as synonyms.) The log odds, and the predicted probabilities, are what are modelled from the logistic regression -- these are results, rather than model inputs. 7 It is conventional to round down to the nearest integer before consulting standard t tables The reason that was a convention is because tables don't have noninteger df. There's no reason to do it otherwise. which makes sense as this adjustment is conservative. Well, the statistic doesn't actually have a t-distribution, because he squared denominator ... 7 Your question touches on both the question of why confidence intervals are not used in these fields, and on the question of why the mean is used in preference to the median even when one would think the median is more appropriate. In psychology (and possibly sociology and urban planning too, but I'm a psychologist, so I have no real idea), no, there are no ... 7 Regression table presentations are easy enough to modify to accommodate tests for equivalence, including relevance tests—where you base conclusions off of both tests for difference (tests of$H^{^{+}}_{0}$) and tests for equivalence (tests of$H^{^{-}}_{0}$). For example (assuming you are presenting multiple tests in a regression context, hence the$\beta\$): ...

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I partly take side with the reviewer on this one. You are interested in the effect of your parameter of interest — given the rest of the model. It is hard to interpret the results and to check the the validity of the model if you only report a single parameter of interest. I would provide: the formula of your model beta estimates for all fixed effects ...

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If you are publishing a paper in the open literature, you should definitely report statistically insignificant results the same way you report statistical significant results. Otherwise you contribute to underreporting bias.

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The first indicates that saving women was probably of high priority (irrespective of whether saving men was) The word "priority" comes from the Latin for "before". A priority is something one comes before something else (where "before" is being used in the sense of "more important"). If you say that saving women was a priority, then saving women has to come ...

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