nlmePredict_RS: Estimation of the reading speed achieved for a given print...

In mnreadR: MNREAD Parameters Estimation and Curve Plotting

Description

This function uses results from the NLME model created with nlmeModel to estimate the reading speed achieved for a specific print size.

Usage

nlmePredict_RS(nlme.model, print.size)

Arguments

nlme.model	The object returned by nlmeModel
print.size	A specific value of print size in logMAR

Value

The function returns a dataframe with a with two variables:

• "print_size" -> the print size value passed to the function (in logMAR)

• "estimated_reading_speed" -> the reading speed achieved at the specified print size as estimated by the NLME model (in words/min)

Notes

The values of print size returned have been corrected for non-standard testing viewing distance.

For more details on the nlme fit, see:\ Cheung SH, Kallie CS, Legge GE, Cheong AM. Nonlinear mixed-effects modeling of MNREAD data. Invest Ophthalmol Vis Sci. 2008;49:828–835. doi: 10.1167/iovs.07-0555.

See Also

nlmeModel to fit MNREAD data using a nonlinear mixed-effect (NLME) modeling

nlmeParam to estimate Maximum Reading Speed (MRS) and Critical Print Size (CPS) from the NLME model

nlmeCurve to plot the individual MNREAD curves estimated from the NLME model

Examples

# inspect the structure of the dataframe
head(data_low_vision, 10)

#------

# restrict dataset to one MNREAD test per subject (regular polarity only)
data_regular <- data_low_vision %>%
    filter (polarity == "regular")

# run the NLME model for data grouped by subject
## Not run:  nlme_model <- nlmeModel(data_regular, ps, vd, rt, err, subject) 

#------

# extract reading speed achieved at 1.6 logMAR according to the NLME fit 
## Not run:  nlmePredict_RS(nlme_model, 1.6) 

mnreadR documentation built on June 25, 2021, 1:07 a.m.