accIndex: Reading ACCessibility Index (ACC) calculation

In mnreadR: MNREAD Parameters Estimation and Curve Plotting

Reading ACCessibility Index (ACC) calculation

Description

This function calculates the Reading Accessibility Index, while applying suited rules for missing data.

Usage

accIndex(data, print_size, reading_time, errors, ... = NULL)

Arguments

data	The name of your dataframe
print_size	The variable that contains print size values for each sentence (print size uncorrected for viewing distance)
reading_time	The variable that contains the reading time for each sentence
errors	The variable that contains the number of errors for each sentence
...	Optional grouping arguments

Value

The function returns a new dataframe with a variable called "ACC" that contains the Reading Accessibility Index estimate.

Notes

The Reading ACCessibility Index (ACC) is a new measure representing an individual's access to text over the range of print sizes found in everyday life. Its calculation does not rely on curve fitting and gives a direct comparison with the performance of normally sighted individuals. The ACC calculation uses the print size values non corrected for non-standard viewing distance.

For more details on the Reading Accessibility Index, see http://doi.org/10.1001/jamaophthalmol.2015.6097

Warning

To ensure that missing data are handled properly and that ACC calculation is correct, data need to be entered along certain rules:

• For the smallest print size that is presented but not read, right before the test is stopped: reading_time = NA, errors = 10

• For all the small sentences that are not presented because the test was stopped before them: reading_time = NA, errors = NA

• If a sentence is presented, and read, but the time was not recorded by the experimenter: reading_time = NA, errors = actual number of errors (cf. s5-regular in low vision data sample)

• If a large sentence was skipped to save time but would have been read well: reading_time = NA, errors = NA (cf. s1-regular in normal vision data sample)

• If a large sentence was skipped to save time because the subject cannot read large print: reading_time = NA, errors = 10 (cf. s7 in low vision data sample)

See Also

mnreadParam for all MNREAD parameters estimation

curveParam_RT for MRS and CPS estimation using values of reading time (instead of reading speed)

curveParam_RS for MRS and CPS estimation using values of reading speed (instead of reading time)

readingAcuity for Reading Acuity calculation

Examples

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

#------

# restrict dataset to one MNREAD test only (subject s1, regular polarity)
data_s1 <- data_low_vision %>%
   filter (subject == "s1", polarity == "regular")

# run the reading accessibility index calculation
data_low_vision_ACC <- accIndex(data_s1, ps, rt, err)

# inspect the newly created dataframe
data_low_vision_ACC

#------

# run the reading accessibility index calculation
# on the whole dataset grouped by subject and polarity
data_low_vision_ACC <- accIndex(data_low_vision, ps, rt, err,
                               subject, polarity)

# inspect the structure of the newly created dataframe
head(data_low_vision_ACC, 10)

mnreadR documentation built on May 29, 2024, 1:34 a.m.