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PanelCheck software features

Here is an overview over features available in our PanelCheck software.

The graphical user interface (GUI)

The graphical user interface of the PanelCheck software was carefully engineered with the help of our partners from the industry. It was designed with focus on simplicity and usability such that valuable information may be accessed with only a few clicks. The implemented statistical methods are sorted according to different type and task (univariate, multivariate, consensus and overall).

The tree control to the left allows for quick generation of plots by double-clicking on any of the tree control contents. Using the checkboxes to the right it is easy to check / un-check assessors, attributes or samples it is only a matter of seconds to re-run the analysis the wanted selection.

Data import

  • PanelCheck accepts text files (.txt), Excel files (.xls) and files with comma separated values (.csv) for data import.
  • Use the built-in drag and drop feature to quickly import the data. 
  • The import dialog provides necessary flexibility for data import. Import only columns that you need from your data set (see screenshot below) through checking and un-checking the respective columns.
  • PanelCheck automatically detects unbalanced data and provides choices for what to strip away from your data set to make it balanced.
  • If you don't want to strip away any of your unbalanced data you may impute the missing part with a method of your choice (using other software) before importing the balanced data set.

Category OVERALL - method: 2-way and 3-way ANOVA

2-way ANOVA (for one or multiple replicates) and 3-way ANOVA (multiple replicates) are integrated in PanelCheck and provide a quick overview over the overall panel performance.

Complimentary LSD plots with dragable / movable significance bars are valuable tools that are convenient for visualisation of sample differences.

Category MULTIVARIATE - method: TUCKER-1 plot

Use Tucker-1 plots to check agreement within your panel.

Category MULTIVARIATE - method: Manhattan plot

Use Manhattan plots to check differences in systematic variation between the panelists using multiple principal components (more than two) at the same time.

Category UNIVARIATE - method: Line Plot

Study details in your raw data by using Line plots.

Category UNIVARIATE - method: Mean & STD plot

Check how your assessors vary in use of scale.

Category UNIVARIATE - method: Correlation plot

Check differences in use of scale, sample ranking, agreement and discrimination ability.

Category UNIVARIATE - method: Profile plot

Provides information on agreement and consensus and individual sample ranking.

Category UNIVARIATE - method: Eggshell plot

Check sample ranking across assessors.

Category UNIVARIATE - method: one-way ANOVA

Information on repeatability and discrimination ability.

F plot provides information on discrimination ability.

MSE plot provides information on repeatability

p*MSE plot provides information on repeatability and discrimination ability.

Category CONSENSUS - PCA on different types of consensus (average across assessors and replicates, standardised, STATIS)

Assessor weights plot showing how much each assessor contributed to the weighted average in STATIS.

Spider plot based on consensus data visualising product differences for each attribute.

Plot export

With PanelCheck it is easy to export all plots directly into PowerPoint presentations.