Apple released a new version of OSX, 10.6 Snow Leopard, on Aug. 28 2009.

Prism 5

We know of one problem using Prism 5.0b on Snow Leopard: Fill patterns don't render well. We recommend that you use solid fills for bars, and simply avoid fill patterns altogether if you use Snow Leopard (and even otherwise, fill patterns are a hold over from the days of plotters, and solid fills look better). It is likely that Apple will fix this glitch in Snow Leopard. If they don't, we'll try to bypass the problem in release 5.0c. 

Other minor glitches:

• Black colors appear gray when the graph is exported to a pdf file using CMYK colors, and viewed in Preview. Choose RGB colors instead, and the pdfs look fine.  Or export a tiff file with CMYK colors. Note that the pdf file is fine, but is just rendered incorrectly by the new version of Preview.
• The Send-to-Powerpoint button and command don't work. Use Copy and Paste instead.
• When running a Prism script, the script log is always empty.
• Editing sheet names in the navigator looks ragged.
• The slider on the info page separating info constants from notes looks corrupted.
• Exporting to the PICT format doesn't work. 
• Exporting using the monochrome color model (to export colorful graphs as black and white) doesn't work.
• If you save a Prism file as XML, its icon is blank.
• One person found that the updater from 5.0a to 5.0b did not work under Snow Leopard. But the full 5.0b installer worked fine.

 We will investigate these problems, and any others we discover or are told about, and fix in release 5.0c coming soon. Let us know if you encounter other problems. 

InStat, StatMate, and Prism 4

InStat 3, StatMate 2 and Prism 4 use an older style of Mac programming. They run perfectly on current macs using an Intel chip, but do so by relying on Apple's Rosetta system. Apple created Rosetta so programs written for the earlier generation of Macs that use a PowerPC chip will also work on newer Intel Macs. This is truly amazing software that just works. You don't even know it is there.

With OSX 10.4 (Tiger) and 10.5 (Leopard), Rosetta was automatically installed and simply works when it is needed. You don't have to configure it, and won't even know when it is running. The only exception is that a few people have had problems after updating to OSX 10.5.6. This page from the Apple web site explains how to fix the problem, which requires running the 'combo update' rather than the 'incremental update' .

Rosetta is not automatically installed with  OSX 10.6 (Snow Leopard). If you are updating to Snow Leopard and plan to run InStat 3, StatMate 2, or Prism 4, click the "Customize" button in the Mac OS X Snow Leopard installer and select the option to install Rosetta. 

If you don't install Rosetta at the time you install Snow Leopard, or get a new Mac without it,  InStat, StatMate and Prism 4 will still work just fine. The first time you run one of these programs under Snow Leopard, OSX detects that you need Rosetta and provides an easy way to install it. You only have to do this once. Rosetta will be installed from Apple's server if you are connected to the internet. Otherwise, you'll need to insert your Mac OS X Snow Leopard installation disc, open the Optional Installs folder, and double-click Optional Installs.

Uniform Requirements for Manuscripts Submitted to Biomedical Journals: Writing and Editing for Biomedical Publications is a lengthy document with guidelines for authors and publishers. But it has only one paragraph about statistics:

"Describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to verify the reported results. When possible, quantify findings and present them with appropriate indicators of measurement error or uncertainty (such as confidence intervals). Avoid relying solely on statistical hypothesis testing, such as P values, which fail to convey important information about effect size. References for the design of the study and statistical methods should be to standard works when possible (with pages stated). Define statistical terms, abbreviations, and most symbols. Specify the computer software used."

These two papers give sensible guidelines for presenting statistical calculations and conclusions:

Curran-Everett and Benos. Guidelines for reporting statistics in journals published by the American Physiological Society. AJP - Gastrointestinal and Liver Physiology (2004) vol. 287 (2) pp. G307. Those authors later published a sequel, with additional comments. This sequel references a bunch of papers which critique the guidelines.

Ludbrook. The presentation of statistics in Clinical and Experimental Pharmacology and Physiology. Clin Exp Pharmacol Physiol (2008) vol. 35 (10) pp. 1271-4). Ludbrook has also self published a two-page set of guidelines for mathematical operators and statistical symbols.  

These authors agree on two points (regarding style, not substance) that I was not aware of, so the GraphPad manuals and help screens (and my book Intuitive Biostatistics) have done differently:

• They say that the standard error of the mean should be abbreviated as SE, rather than SEM.
• They say that the mean and standard deviation should be written as mean (SD), rather than mean ± SD. if the mean is 11.2 and the standard deviation is 2.4, they suggest reporting 11.2 (2.4) rather than 11.2  ± 2.4. They recommend using that latter syntax only for standard errors, not standard deviations. 

 

If you choose (or accept the default) standard weighting, then the residuals are the difference between the actual Y value you entered and the Y value predicted by the model. If the data point is above the curve, the residual is positive. If the data point is below the curve, the residual is negative.  Least-squares regression works to minimize the sum of the squares of these residuals. 

If you choose another weighting scheme, Prism 5 adjusts the definition of the residuals accordingly. The residual that Prism tabulates and plots equals the residual defined in the prior paragraph, divided by the weighting factor.  The most common common alternative weighting is "Weight by 1/Y² (minimize relative distances squared)". In this case, the residual is defined to be the distance of the point from the curve divided by the Y value of the curve. Weighted nonlinear regression minimizes the sum of these residuals squared.

Note the ambiguity in defining weighting. The Prism dialog gives the choice to weight by 1/Y². This means that the squared residual is divided by Y². The weighted residual is defined as the residual divided by Y. Prism minimizes the sum of the squares of these weighted residuals.

Earlier versions of Prism (up to Prism 4) always plotted basic unweighted residuals, even if you chose to weight the points unequally. 

When performing linear regression, Prism does not offer weighting so the residuals are always unweighted residuals as defined in the first paragraph above. 

How Prism computes R² with weighted nonlinear regression. 

How weighted nonlinear regression works.

 Many people ask why multiple comparisons tests following one-way (or two-way) ANOVA can't report individual P values for each comparison. When you correct for multiple comparisons, it really doesn't make much sense to talk about individual P values. All you can do is divide the comparisons into two groups -- statistically significant and not -- at some defined significance level (usually 5%) that applies to the entire family of comparisons. 

However SAS reports adjusted P values, and these are explained in the book by Westfall  (citation below).

The idea is pretty simple. There is nothing special about 0.05 or 0.01... You can set the significance level to any probability you want. The adjusted P value is the smallest probability at which a particular comparison will be declared statistically significant (as part of the multiple comparison testing). Each comparison will have a unique adjusted P value. But these P values are computed from all the comparisons, and really can't be interpreted for just one comparison. 

Computing the adjusted P value is trivial for Bonferroni multiple comparison tests. It is harder for Tukey and Dunnett tests, as it requires computing critical values beyond those that have been tabulated. 

We are considering including adjusted P values as part of the reporting of one-way ANOVA with Tukey, Bonferroni or Dunnett multiple comparison tests. I hesitate to do this (the programming is far from trivial) because I don't really know how to explain how to interpret the results, and fear that they will be misinterpreted. 

I don't know of any program except SAS that computes adjusted P values, and don't know of any book except Westfall that explains them. They do not seem to be mainstream. 

Please let us know if you would like to see adjusted P values in future versions of Prism, and explain why.

	Multiple Comparisons and Multiple Tests (Text and Workbook Set)
	by Peter H. Westfall, Randall D. Tobias, Dror Rom
	IBSN:1580258336. List price:$62.32
	Buy from amazon.com for $50.18

Prism 5.02 (Windows) and 5.0b (Mac) included a fix to a trivial bug in Fisher's exact test (when the two groups are identical, the P value should be 1.00 but earlier versions of Prism sometimes reported P values slightly greater than 1.0). Unfortunately, that fix introduced a new bug that occurs only when:

• You are using Prism 5.02 (Windows) or 5.0b (Mac). Earlier versions did not have this bug. Neither does InStat 3.0 or 3.1. 
• You have entered a symmetrical contingency table. A table is symmetrical when either the two row totals are identical, or the two column totals are identical. 
• You have chosen a two-tail (two-sided) P value. One-tail P values are computed correctly. 

The result of the bug is that the P value will be too low in some, but not all cases. In many cases, the discrepancy is tiny and won't affect your conclusions. In other cases, the discrepancy is larger and may affect your conclusion.

Of course, we will fix the bug in the next release of Prism: 5.03 and 5.0c.

It is easy to determine whether you have encountered this bug, and to compute the correct two-tail P value. With symmetrical contingency tables, the two-tail P value is exactly twice the one-tail P value (that is not always true with contingency tables that are not symmetrical). Therefore, to bypass the bug, ask Prism to compute a one-tail (one-sided) P value. This is a choice in the Parameters dialog for analyzing contingency table. To compute a two-tail P value, simply double the one-tail P value. 

More details and example.