Description
MNREAD Parameters Estimation and Curve Plotting.
Description
Allows to analyze the reading data obtained with the MNREAD Acuity Chart, a continuous-text reading acuity chart for normal and low vision. Provides the necessary functions to plot the MNREAD curve and estimate automatically the four MNREAD parameters: Maximum Reading Speed, Critical Print Size, Reading Acuity and Reading Accessibility Index. Parameters can be estimated either with the standard method or with a nonlinear mixed-effects (NLME) modeling. See Calabrese et al. 2018 for more details <doi:10.1167/18.1.8>.
README.md
mnreadR
The goal of mnreadR is to analyze MNREAD data using R.
The MNREAD Acuity Charts are continuous-text reading acuity charts for normal and low vision.
The charts are used to assess how reading performance depends on print size. Four measures of reading performance are obtained: Reading acuity (the smallest print that can be read); Maximum reading speed (the reading speed when performance is not limited by print size); Critical print size (the smallest print that supports the maximum reading speed) and Reading accessibility index (a single measure that represents one’s visual access to printed material)
The four MNREAD parameters are usually estimated by hand by plotting reading speed as a function of print size. The present package will provide all necessary functions to perform this estimation automatically in R.
The MNREAD Acuity Charts have a wide range of applications in testing normal and low vision: prescribing optical corrections for reading, or other near tasks in the eye clinic, in low vision assessment, prescribing magnifiers or other reading aids, applications in pediatrics and special education, and research. The MNREAD test is widely used as an outcome measure in clinical trials of treatements for vision disorders. By providing standardized and automated methods to analyze the reading test results, this package will be useful for both the research and medical communities.
Installation
You can install the released version of mnreadR from CRAN with:
install.packages("mnreadR")
Example
This is a basic example which shows you how to solve a common problem:
library(mnreadR)
#> Loading required package: dplyr
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
#> Loading required package: tidyr
#> Loading required package: ggplot2
#> Welcome to the MNREAD R package!
# inspect the structure of the dataframe
head(data_low_vision, 10)
#> subject polarity treatment vd ps rt err
#> 1 s1 regular A 20 1.3 6.66 0
#> 2 s1 regular A 20 1.2 6.53 0
#> 3 s1 regular A 20 1.1 7.46 0
#> 4 s1 regular A 20 1.0 11.69 0
#> 5 s1 regular A 20 0.9 11.16 0
#> 6 s1 regular A 20 0.8 12.75 0
#> 7 s1 regular A 20 0.7 23.09 0
#> 8 s1 regular A 20 0.6 34.62 1
#> 9 s1 regular A 20 0.5 NA 10
#> 10 s1 regular A 20 0.4 NA NA
# run the parameters estimation
data_low_vision_param <- mnreadParam(data_low_vision, ps, vd, rt, err,
subject, polarity)
#> Remember to check the accuracy of MRS and CPS estimates by inspecting the MNREAD curve with mnreadCurve()
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning: There was 1 warning in `reframe()`.
#> ℹ In argument: `max(rs)`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Warning in log(omax): NaNs produced
#> Joining with `by = join_by(subject, polarity)`
#> Joining with `by = join_by(subject, polarity)`
What is special about using README.Rmd instead of just README.md? You can include R chunks like so:
summary(cars)
#> speed dist
#> Min. : 4.0 Min. : 2.00
#> 1st Qu.:12.0 1st Qu.: 26.00
#> Median :15.0 Median : 36.00
#> Mean :15.4 Mean : 42.98
#> 3rd Qu.:19.0 3rd Qu.: 56.00
#> Max. :25.0 Max. :120.00
You’ll still need to render README.Rmd regularly, to keep README.md up-to-date.
You can also embed plots, for example:
In that case, don’t forget to commit and push the resulting figure files, so they display on GitHub!