JMP^® Screenshots

JMP - Create a variety of bar charts and add error bars, with the interactive Graph Builder.

JMP - Box plots and other types of graphs are available from Graph Builder.

JMP - Visualize changes over time using Bubble Plots.

JMP - Analyze process capability using the Distribution platform.

Build custom menus to quickly access your data or custom applications.

Analyze complex surveys with complete control of question structures, report presentation and statistical tests performed.

The advanced neural network capabilities in JMP Pro include the choice of three activation functions and two layers, a choice of validation methods, as well as gradient boosting.

Advanced features for partial least squares (PLS) regression in the Fit Model platform. Model effects can include categorical factors, as well as crossed and polynomial terms.

Build cross-validated boosted decision-tree models, which build many simple trees, repeatedly fitting any residual variation from one tree to the next.

The bootstrap forest technique grows dozens of decision trees using random subsets of the available data and then averages the computed influence of each factor in these trees.

Stepwise regression includes the option of stopping rules based on cross-validation.

JMP Pro includes advanced computational methods for performing exact measures of association and oneway nonparametric exact tests.

Use Generalized Regression in JMP Pro to build better predictive models despite data challenges.

Compare the effect of different architectures on a neural fit with boosting (left) and without (right).

Partial least squares (PLS) regression can impute missing data before fitting.

Build and fit mixed models to analyze data that involves both time and space.

Model comparision provisions for comparing fits across multiple fit predictions.

Build multi-layer, cross-validated neural network models with numerous architectures.

Bootstrap any statistic in a JMP report with a single click. This example shows bootstrapping confidence limits around a 10th percentile quantile.

Use the Reliability Block Diagram for complex system design and to locate and address weaknesses in the system.

Uplift models identify the consumer segments most likely to respond favorably to an offer or treatment.

Easily split your data into training, validation and test portions for honest assessment of a model’s predictive ability.

Use variable clustering for quick and easy dimension reduction to make your prediction problems easier to solve.

Severity analysis of adverse events shows differences across treatment groups via dynamically linked graphs.

Tree maps like this one can show whether drug-event pairs meet signal criteria.

A simplified Starter menu helps users easily choose specific reports and analyses for dynamic visual exploration.

From one-way plots, select subjects of interest and drill down again to patient profiles.

This distribution shows duration of exposure for all subjects in the trial.

A Hierarchical Cluster report with two-way clustering identifies relationships between individual subjects and the events, findings and interventions included in the safety analyses for the study.

A two-dimensional hierarchical cluster shows relationships between selected events, findings or observations.

Zoom in to select subjects in the Hy’s Law region. Drill down on selected subjects to see patient profiles or subject clusters.

The default view for the JMP Clinical bubble plot is a representation of Hy’s Law analysis, showing changes across treatment groups over time for any lab.

The industry-standard Hy’s Law display in JMP Clinical is interactive for selection of subjects. A dashboard containing a scatterplot matrix of transaminases and bilirubin; mosaic plot of days until bilirubin elevation and missing lab tests report tab.

The mapping feature in Graph Builder lets you choose any variable for geographic display.

A new medical monitors dashboard in JMP Clinical 4 displays frequency and count information for adverse events.

Use Graph Builder’s Mosaic Plot to compare adverse events, here from the vascular body system, by sex across treatment groups.

Use the zoom tool in JMP Clinical to magnify clusters of interest, and then run a partial correlation analysis on any items in the cluster.

A patient profile dashboard allowing configuration of clinical information, notes for reviewers and printing to PDF documents.

Easily display the relative risk of significant adverse events.

In this bubble plot, time windows show the change in significance and relative risk for all adverse events and concomitant medications for each day of the trial.

From the volcano plot, drill down to a relative risk plot to sort easily by count, relative risk, significance or dictionary-derived terms.

From the severity analysis, select significant adverse events and drill down to the subject level with one-way plots.

A trellis plot graphs trends for selected subjects of interest.

From the volcano plot, a Venn diagram helps identify co-occurring adverse events for subjects in the study. Then select subjects for clustering or profiling.