Description Usage Arguments Value Warning References Examples
automated_readability_index
- Apply Automated
Readability Index to transcript(s) by zero or more
grouping variable(s).
coleman_liau
- Apply Coleman Liau Index to
transcript(s) by zero or more grouping variable(s).
SMOG
- Apply SMOG Readability to transcript(s) by
zero or more grouping variable(s).
flesch_kincaid
- Flesch-Kincaid Readability to
transcript(s) by zero or more grouping variable(s).
fry
- Apply Fry Readability to transcript(s) by
zero or more grouping variable(s).
linsear_write
- Apply Linsear Write Readability to
transcript(s) by zero or more grouping variable(s).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | automated_readability_index(text.var,
grouping.var = NULL, rm.incomplete = FALSE, ...)
coleman_liau(text.var, grouping.var = NULL,
rm.incomplete = FALSE, ...)
SMOG(text.var, grouping.var = NULL, output = "valid",
rm.incomplete = FALSE, ...)
flesch_kincaid(text.var, grouping.var = NULL,
rm.incomplete = FALSE, ...)
fry(text.var, grouping.var = NULL, labels = "automatic",
rm.incomplete = FALSE, ...)
linsear_write(text.var, grouping.var = NULL,
rm.incomplete = FALSE, ...)
|
text.var |
The text variable. |
grouping.var |
The grouping variables. Default NULL generates one output for all text. Also takes a single grouping variable or a list of 1 or more grouping variables. |
rm.incomplete |
logical. If TRUE removes incomplete sentences from the analysis. |
... |
Other arguments passed to
|
output |
A character vector character string indicating output type. One of "valid" (default and congruent with McLaughlin's intent) or "all". |
labels |
A character vector character string
indicating output type. One of |
Returns a dataframe with selected readability statistic
by grouping variable(s). The frey
function
returns a graphic representation of the readability as
well as a list of two dataframe: 1) SENTENCES_USED
and 2) SENTENCE_AVERAGES
.
Many of the indices (e.g. Automated Readability Index) are derived from word difficulty (letters per word) and sentence difficulty (words per sentence). If you have not run the sentSplit function on your data the results may not be accurate.
Coleman, M., & Liau, T. L. (1975). A computer readability formula designed for machine scoring. Journal of Applied Psychology, Vol. 60, pp. 283-284.
Flesch R. (1948). A new readability yardstick. Journal of Applied Psychology. Vol. 32(3), pp. 221-233. doi: 10.1037/h0057532.
Gunning, T. G. (2003). Building Literacy in the Content Areas. Boston: Allyn & Bacon.
McLaughlin, G. H. (1969). SMOG Grading: A New Readability Formula. Journal of Reading, Vol. 12(8), pp. 639-646.
Senter, R. J., & Smith, E. A.. (1967) Automated readability index. Technical Report AMRLTR-66-220, University of Cincinnati, Cincinnati, Ohio.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | AR1 <- with(rajSPLIT, automated_readability_index(dialogue, list(person, act)))
htruncdf(AR1,, 15)
AR2 <- with(rajSPLIT, automated_readability_index(dialogue, list(sex, fam.aff)))
htruncdf(AR2,, 15)
CL1 <- with(rajSPLIT, coleman_liau(dialogue, list(person, act)))
head(CL1)
CL2 <- with(rajSPLIT, coleman_liau(dialogue, list(sex, fam.aff)))
head(CL2)
SM1 <- with(rajSPLIT, SMOG(dialogue, list(person, act)))
head(SM1)
SM2 <- with(rajSPLIT, SMOG(dialogue, list(sex, fam.aff)))
head(SM2)
FL1 <- with(rajSPLIT, flesch_kincaid(dialogue, list(person, act)))
head(FL1)
FL2 <- with(rajSPLIT, flesch_kincaid(dialogue, list(sex, fam.aff)))
head(FL2)
FR <- with(rajSPLIT, fry(dialogue, list(sex, fam.aff)))
htruncdf(FR$SENTENCES_USED)
head(FR$SENTENCE_AVERAGES)
LW1 <- with(rajSPLIT, linsear_write(dialogue, list(person, act)))
head(LW1)
LW2 <- with(rajSPLIT, linsear_write(dialogue, list(sex, fam.aff)))
head(LW2)
|
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