What's new in Prism 6 ?

New Analyses – ANOVA, multiple comparisons and more

• Two-way ANOVA with repeated measures in both factors.
• Multiplicity adjusted (“exact”) P values for multiple comparison tests. Read more about this #1 request in our blog.
• New post tests - Fisher’s unprotected Least Significant Difference (LSD) and Holm-Sidak.
• Run a set of t tests (one per row) at once, correcting for multiple comparisons with Bonferroni or by contolling the False Discovery Rate (FDR).
• Follow two-way ANOVA with tests for simple or main effects. Don't worry if you don't know what that means - Prism 6 presents those choices graphically so the meaning is obvious.
• Greenhouse-Geisser correction in repeated measures one-way ANOVA to avoid the need to assume sphericity.
• Grubbs’ outlier detection. Our most popular QuickCalc web calculator is now part of Prism.
• Kolmogorov-Smirnov test to compare two groups (an alternative to the Mann-Whitney test).
• Ratio t test

Improved curve fitting

• Fit to implicit and differential models.
• Write more complex models.
• Quicker interpolations. Prism 6 adds a new analysis that streamlines the process of interpolating values from standard curves.
• Weight your fit by 1/Y^k
• Monte-Carlo simulations without writing scripts.

Pie charts and more

• Prism 6 adds a new kind of data table for parts of whole data. Plot pie charts, donut plots and more.
• Compare the observed distribution of values with theoretically expected values with the chi-squared or binomial test.
• Compute each value as a fraction or percentage of the column total.

Work with larger data sets

• Enter data in up to 256 data set columns.
• Enter up to 256 subcolumns per data set (up from 52 in Prism 5). This lets you compute repeated measures two-way ANOVA with more subjects.

Work mor efficiently

• Faster. Faster saving, faster closing, faster nonparametric calculations, faster graphing, faster, crisper screen redraws.
• Format several data sets at once. Want to plot alternating columns as dotted lines? Now you can do it in one step.
• View and edit all of your column titles at once. Great for large files!
• Choose the size, shape and color of your data points right from the data table. You can even select any contiguous block of data and make choices for that specific subset of your data table.
• WAND. If you love MAGIC, you will love the new WAND. While MAGIC reformats graphs, the WAND analyzes and graphs a new data table to match what you have done to another.
• Paste link values from results tables into a data table so everything updates automatically. This also works if you want to link data from one data table to another.

More ways to customize your graphs and layouts

Improved Exporting/Importing

• Export graphs in more formats.
• Better TIFF compression means smaller files and faster exporting.
• Import more types of graphic files into your Prism layouts.
• Control whether to use periods or commas as a decimal separator from within Prism.
• Choose how to handle excluded values when you export/paste from Prism data tables.
• If you use LabArchives, you can now open your Prism files right from LabArchives without first downloading the files to your computer. Prism 6 files are fully searchable within LabArA

Statistical Features of Prism 6

Statistical comparisons

• Paired or unpaired t tests. Reports P values and confidence intervals.
• Nonparametric Mann-Whitney test, including confidence interval of difference of medians.
• Kolmogorov-Smirnov test.
• Wilcoxon test with confidence interval of median.
• Perform many t tests at once, using False Discover Rate to choose which comparisons are discoveries to study further.
• Ordinary or repeated measures one-way ANOVA followed by the Tukey, Newman-Keuls, Dunnett, Bonferroni or Holm-Sidak multiple comparison tests, the post-test for trend, or Fisher’s Least Significant tests.
• Many multiple comparisons test are accompanied by confidence intervals and multiplicity adjusted P values.
• Greenhouse-Geisser correction so repeated measures one-way ANOVA does not have to assume sphericity. When this is chosen, multiple comparison tests also do not assume sphericity.
• Kruskal-Wallis or Friedman nonparametric one-way ANOVA with Dunn's post test.
• Fisher's exact test or the chi-square test. Calculate the relative risk and odds ratio with confidence intervals.
• Two-way ANOVA, even with missing values with some post tests.
• Two-way ANOVA, with repeated measures in one or both factors. Tukey, Newman-Keuls, Dunnett, Bonferron, Holm-Sidak, or Fishers LSD multiple comparisons testing main and simple effects.
• Kaplan-Meier survival analysis. Compare curves with the log-rank test (including test for trend).

Column statistics

• Calculate min, max, quartiles, mean, SD, SEM, CI, CV,
• Mean or geometric mean with confidence intervals.
• Frequency distributions (bin to histogram), including cumulative histograms.
• Normality testing by three methods.
• One sample t test or Wilcoxon test to compare the column mean (or median) with a theoretical value.
• Skewness and Kurtosis.
• Identify outliers using Grubbs or ROUT method.

Linear regression and correlation

• Calculate slope and intercept with confidence intervals.
• Force the regression line through a specified point.
• Fit to replicate Y values or mean Y.
• Test for departure from linearity with a runs test.
• Calculate and graph residuals.
• Compare slopes and intercepts of two or more regression lines.
• Interpolate new points along the standard curve.
• Pearson or Spearman (nonparametric) correlation.

Nonlinear regression

• Fit one of our 105 built-in equations, or enter your own.
• Enter differential or implicit equations.
• Enter different equations for different data sets.
• Global nonlinear regression – share parameters between data sets.
• Robust nonlinear regression.
• Automatic outlier identification or elimination.
• Compare models using extra sum-of-squares F test or AICc.
• Compare parameters between data sets.
• Apply constraints.
• Differentially weight points by several methods.
• Accept automatic initial estimated values or enter your own.
• Automatically graph curve over specified range of X values.
• Quantify precision of fits with SE or CI of parameters.
• Quantify symmetry of inprecision with Hougaard’s skewness.
• Plot confidence or prediction bands.
• Test normality of residuals.
• Runs or replicates test of adequacy of model.
• Report the covariance matrix or set of dependencies.
• Easily interpolate points from the best fit curve.

Clinical (diagnostic) lab statistics

• Bland-Altman plots
• Receiver operator characteristic (ROC) curves
• Deming regression (type ll linear regression)

Prism 6 – Automation

There are four different approaches to automation in PRISM. All of those four approaches can help you dealing more effectively, quickly and safely with routine tasks. For each section in the workflow you have an automation variant.

Wand and Magic

If you love MAGIC, you will love the new WAND. While MAGIC reformats graphs, the WAND analyzes and graphs a new data table to match what you have done to another.

If you've already entered data onto an empty data table, it is too late to clone, too late to duplicate a family, and too late to open a template -- at least without copy and pasting data. Prism provides a great tool to solve this problem: the Wand (Wizard to ANalyze Data). Use it to analyze (and graph) the new table just like you already analyzed (and graphed) an existing table.

Prism Magic makes graphs consistent. Use the Prism Magic tool in the Change section of the Prism toolbar to make one graph look like another. You can choose any recently-used graph, any graph in an open project, or any graph saved as an example.

Templates

A template is a Prism file that you recycle. Choose a template, add new data, and all the analyses and graphs will be created automatically. Templates are an older feature, and we recommend you clone a graph, or use the Wand, instead.

• A template has the extension .pzt. When Prism opens such a file, it will "forget" the file name and open the file without a name. Then it will prompt for a file name when you save. This prevents accidentally overwriting the template.
• When you save a template, you can enter some brief instructions that will appear when the template is opened. This can be useful when you are creating a template for others to use.
• A list of templates will appear on the Open a File tab of the Welcome dialog.

Methods

If you've already entered data onto an empty data table, it is too late to using cloning or templates -- at least without copy and pasting. But it is not too late to apply a method to your data. Effectively, this means telling Prism to analyze (and graph) the new table just like you already analyzed (and graphed) an existing one. This is called using a Method. Method is comparable to Wand. The difference is: a Method is like a Template pre saved.

Prism 6 Help System

Besides the help system which can be seen as a comprehensive software- and statistics reference PRISM also adds extensive benefits:

Welcome Dialog (figure)

The welcome dialog functions as the central steering system for PRISM. It defines the different project types which trigger different types of graphs as well as different statistical analysis. The help systems offers a quick overview of the areas of application for each project type. A simple click on "Learn more"reveals a comprehensive and concise description for each project type.

Learn (figure)

The welcome dialog functions as the central steering system for PRISM. It defines the different project types which trigger different types of graphs as well as different statistical analysis. The help systems offers a quick overview of the areas of application for each project type. A simple click on "Learn more"reveals a comprehensive and concise description for each project type.

Analysis Checklist (figure)

The new help system adds another focal point. After running an analysis you often ask yourself: “are these results valid”? The "Analysis Checklist", which is available for every built in statistical analysis, is our answer. To ensure the validity of your results, all you need to do is walk through the steps outlined in the checklist. The checklist is sorted, so that the first entry shows the “worst” violation of analysis assumptions. The following entries in the list range to the least „problematic“ assumption violation.