ROIstat v2.02 Released

We released a new minor update fixing a couple of bugs. One caused a lockup when doing sample size calculations and entering an alpha of zero. The other displayed the wrong sample size when doing a one-sample variance test.


If you haven't already downloaded ROIstat v 2, it is a huge update! ROIstat 2 adds the ability to make and analyze statistical process control charts.

You can download it here:

Download ROIstat!

(ROIstat Changelog)

  • In order to fix an irrelevant console error in one of the packages, load a fresh RStudio instance and type:
    • install.packages("devtools")
    • require(devtools)
    • remotes::install_github("dreamRs/shinyWidgets")
  • Fixed error with oneway ANOVA post-hoc that could cause test to fail if factors were defined as factors
  • Fixed unlikely but possible error in random-effects ANOVA (if the between sample MS is less than the within-sample MS the sample to sample variance and ICC would be negative)
  • Fixed a bug that would break parts of the EDA section, the Oneway ANOVA, and scatterplots if the column titles were not syntactically valid (e.g. had a space)
  • Fixed a bug in calculating the natural tolerance for exponential distributions
  • Added the ability to download scatterplots in a variety of publication-ready formats
  • Added the ability to hover over a point on a scatterplot to get its x and y location
  • Moved the scatterplot equation model to a title on the graph so that it downloads with the graph. This is the actual model used in the non-linear regression and plotted, not the transformed data model used in the correlation analysis below it
  • Added option in EDA Natural Tolerance for exponential with 0 low
  • Added SPC charts
    • Added SPC for variables data
      • Data can be column or row format
      • A column can be used to designate "sets" of data that should be analyzed together. Sets do not have to be contiguous.
      • You can select either 2 or 3 standard errors for charts, with the default being 3
      • You can select X-bar charts and use various limit calculations and use the mean or median as a centerline. The limits below are similar across the variables charts:
        • Average Range - Good at robustly estimating the underlying process
        • Median Range - Good at robustly estimating the underlying process if the range has some unexplained out of control points
        • Average Standard Deviation Within Samples - Good if you are really sure that your process is in control
        • Median Standard Deviation Within Samples - Good if you are really sure that your process is in control but a few samples are unusually variable
        • Average Variance - Good if you are really sure that your process is in control and you are a statistician
        • Average Moving Range of the X-bars - Good for when the within-sample variability does not predict the between-sample variability. For example, stratified processes or setup-dependent processes.
        • Median Moving Range of the X-bars - Good for when the within-sample variability does not predict the between-sample variability but there are unexplained jumps in the means. For example, stratified processes or setup-dependent processes.
        • Standard Deviation of the X-bars - Good for when the within-sample variability does not predict the between-sample variability and you are really sure that the between-sample variability is in control.
        • Known s - Good for when you have a lot of data and evidence that the process produces normally distributed data that is in control and you know the true standard deviation. Mostly present to show why it is a bad idea to do this in a real process.
        • Custom limits - Good for when you have known limits from previous data. Also how to enter limits from distribution fits.
      • Range with various limit and variance estimate calculations and use the mean or median as a centerline.
      • Standard deviation with various limit and variance estimate calculations and use the mean or median as a centerline.
      • Variance with various limit and variance estimate calculations and use the mean or median as a centerline.
      • Selecting a method for the dispersion calculation will automatically suggest matching centerlines and matching limit calculations. These defaults can be changed.
      • All variables charts can generate a brief analysis that shows how the limits were calculated, what the total standard deviation of all the individuals is, what the standard deviation of individuals within each set is, and what the estimated standard deviation is for the process based on the dispersion method selected. The correlation between the location and dispersion chart is tested for significance. If you enter specifications, you will also get capability measures (Cp, Cpk, Cpm) based on the estimated standard deviation, process performance measures (Pp, Ppk, Ppm) based on the observed standard deviation, and predicted and actual parts non-conforming. For means, a oneway random-effects analysis is also performed to see if there are additional sources of variation present between samples beyond the within variability. For individuals, autocorrelation is tested.
    • Added SPC charts for attributes data
    • Data where each observation is a row
      • p charts. The limits below are similar across the attributes charts.
        • Exact binomial for p and np charts (exact Poisson for c and u charts)
        • Normal approximation
        • Average moving range
        • Median moving range
        • Standard deviation
        • Custom limits
      • np charts
      • c charts
      • u charts
    • All SPC charts can be downloaded in a variety of publication-ready formats
    • All SPC chart data can be displayed should you wish to save it, including the results of the various out of control rules
    • All SPC charts allow you to get information about each point by hovering the mouse near the point
    • All SPC charts can select from various out-of-control rules including zone rules. The run rule can be 8 or 9 points. Mean and dispersion charts can use different rule sets.
    • All SPC charts can display control zones
    • All SPC charts can be modified by showing or hiding
      • Lines connecting points
      • Control limits
      • Centerlines
      • Labels indicating the type of control violation for a point
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