mnreadR (version 2.1.7)

nlmeParam: Maximum Reading Speed (MRS) and Critical Print Size (CPS) estimation using a nonlinear mixed-effect (NLME) modeling.

Description

This function uses the NLME model created from nlmeModel to extract the following MNREAD parameters:

• Maximum Reading Speed (MRS)

• Critical Print Size (CPS)

Usage

nlmeParam(nlme.model, CPScriterion = NULL)

Value

The function returns a new dataframe with two variables:

• "CPS" -> contains the Critical Print Size estimate (in logMAR)

• "MRS" -> contains the Maximum Reading Speed estimate (in words/min)

Arguments

nlme.model

The object returned by nlmeModel

CPScriterion

Optional argument to specify a criterion for CPS estimation. The default criterion value is '90 of MRS'. This criterion can vary from 75 to 95 of MRS and should only be modified for specific purposes, as discussed in Cheung et al. 2008

Notes

To ensure proper estimation of the MRS and CPS, individual MNREAD fit should be plotted using nlmeCurve and inspected visually. If some of the estimated values of MRS and CPS seem off given the actual data, we advise you to run mnreadCurve and overwrite these estimates with values estimated visually from the actual MNREAD curve.

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

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

curveParam_RT for standard estimation of MRS and CPS

mnreadParam for all MNREAD parameters estimation

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
 nlme_model <- nlmeModel(data_regular, ps, vd, rt, err, subject) 

#------

# run the parameters' estimation for a default CPS criterion of '90 of MRS' 
 nlmeParam(nlme_model) 

# run the parameters' estimation for a specific CPS criterion of '80 of MRS'
 nlmeParam(nlme_model, 0.8)