Meanscore method for missing covariate data in logistic regression models
Marie Reilly PhD <marie.reilly@ucc.ie> and Agus Salim <a.salim@ucc.ie>
The Mean Score method for missing and auxiliary covariate data
is described in the paper by Reilly & Pepe in Biometrika 1995.
This likelihood-based method allows an analysis using all available
cases and hence will give more efficient estimates.
The method is applicable to cohort or case-control designs.

Marie Reilly PhD <marie.reilly@ucc.ie> and Agus Salim <agus@stat.ucc.ie>

Marie Reilly PhD <marie.reilly@meb.ki.se> and Agus Salim <a.salim@cgiar.org>

Make Quick Descriptive Tables for Continuous Variables
Quickly make tables of descriptive statistics (i.e., counts,
means, confidence intervals) for continuous variables. This
package is designed to work in a Tidyverse pipeline, and consideration
has been given to get results from R to 'Microsoft Word' ® with minimal pain.

Detection and Control of Tree-Ring Widths on Scanned Image
Sections of Dendrochronological Samples
Wilson Lara <wilarhen@gmail.com>, Carlos Sierra <csierra@bgc-jena.mpg.de>
This package assists in the identification of ring borders on scanned image sections from dendrochronological samples. It processes the image section and computes luminance data from images producing a matrix of gray values and a time series of smoothed gray values. Luminance data is plotted on segmented images for users to perform both: visual identification of ring borders, or control of automatic detection. The package provides functions to visually include/exclude ring borders on the R graphical device, or automatically detect ring borders using a linear detection algorithm. This algorithm detects ring borders according to negative extreme values in the smoothed time-series of gray values.

Detection and Control of Tree-Ring Widths on Scanned Image
Sections
Wilson Lara, Carlos Sierra, Felipe Bravo
Identification of ring borders on scanned image sections from dendrochronological samples. Processesing of image reflectances to produce gray matrices and a time series of smoothed gray values. Luminance data is plotted on segmented images for users to perform both: visual identification of ring borders, or control of automatic detection. Routines to visually include/exclude ring borders on the R graphical device, or automatically detect ring borders using a linear detection algorithm. This algorithm detects ring borders according to positive/negative extreme values in the smoothed time-series of gray values.