This dataset contains data from a self-paced reading experiment on Chinese relative clause comprehension. It is structured to support analysis of reaction times, comprehension accuracy, and surprisal values across various experimental conditions in a 2x2 fully crossed factorial design:
Usage
data(df_jaeger14)Format
A tibble with 8,624 rows and 15 variables:
- subject
Participant identifier, a character vector.
- item
Trial item number, an integer.
- cond
Experimental condition, a character vector indicating variations in sentence structure (e.g., "a", "b", "c", "d").
- word
Chinese word presented in each trial, a character vector.
- wordn
Position of the word within the sentence, an integer.
- rt
Reaction time in milliseconds for reading each word, an integer.
- region
Sentence region or phrase type (e.g., "hd1", "Det+CL"), a character vector.
- question
Comprehension question associated with the trial, a character vector.
- accuracy
Binary accuracy score for the comprehension question (1 = correct, 0 = incorrect).
- correct_answer
Expected correct answer for the comprehension question, a character vector ("Y" or "N").
- question_type
Type of comprehension question, a character vector.
- experiment
Name of the experiment, indicating self-paced reading, a character vector.
- list
Experimental list number, for counterbalancing item presentation, an integer.
- sentence
Full sentence used in the trial with words marked for analysis, a character vector.
- surprisal
Model-derived surprisal values for each word, a numeric vector.
Region codes in the dataset (column region):
N: Main clause subject (in object-modifications only)
V: Main clause verb (in object-modifications only)
Det+CL: Determiner+classifier
Adv: Adverb
VN: RC-verb+RC-object (subject relatives) or RC-subject+RC-verb (object relatives)
Note: These two words were merged into one region after the experiment; they were presented as separate regions during the experiment.
FreqP: Frequency phrase/durational phrase
DE: Relativizer "de"
head: Relative clause head noun
hd1: First word after the head noun
hd2: Second word after the head noun
hd3: Third word after the head noun
hd4: Fourth word after the head noun (only in subject-modifications)
hd5: Fifth word after the head noun (only in subject-modifications)
Notes on reading times (column rt):
The reading time of the relative clause region (e.g., "V-N" or "N-V") was computed by summing up the reading times of the relative clause verb and noun.
The verb and noun were presented as two separate regions during the experiment.
Source
Jäger, L., Chen, Z., Li, Q., Lin, C.-J. C., & Vasishth, S. (2015). The subject-relative advantage in Chinese: Evidence for expectation-based processing. Journal of Memory and Language, 79–80, 97-120. https://doi.org/10.1016/j.jml.2014.10.005
Details
Factor I: Modification type (subject modification; object modification)
Factor II: Relative clause type (subject relative; object relative)
Condition labels:
a) subject modification; subject relative
b) subject modification; object relative
c) object modification; subject relative
d) object modification; object relative
See also
Other datasets:
df_sent
Examples
# Basic exploration
head(df_jaeger14)
#> # A tidytable: 6 × 14
#> subject item cond word wordn rt region question accuracy correct_answer
#> <chr> <int> <chr> <chr> <int> <int> <fct> <chr> <int> <int>
#> 1 1m1 1 a 那個 1 360 Det+CL 那個顧客聽說過… 1 1
#> 2 1m1 1 a 昨晚 2 359 Adv 那個顧客聽說過… 1 1
#> 3 1m1 1 a 揍了服務生… 3 344 VN 那個顧客聽說過… 1 1
#> 4 1m1 1 a 一頓 4 313 FreqP 那個顧客聽說過… 1 1
#> 5 1m1 1 a 的 5 297 DE 那個顧客聽說過… 1 1
#> 6 1m1 1 a 顧客 6 312 head 那個顧客聽說過… 1 1
#> # ℹ 4 more variables: question_type <int>, experiment <chr>, list <int>,
#> # sentence <chr>
# Summarize reaction times by region
library(tidytable)
df_jaeger14 |>
group_by(region) |>
summarize(mean_rt = mean(rt, na.rm = TRUE))
#> # A tidytable: 13 × 2
#> region mean_rt
#> <fct> <dbl>
#> 1 N 614.
#> 2 V 538.
#> 3 Det+CL 513.
#> 4 Adv 541.
#> 5 VN 618.
#> 6 FreqP 603.
#> 7 DE 439.
#> 8 head 653.
#> 9 hd1 604.
#> 10 hd2 538.
#> 11 hd3 704.
#> 12 hd4 479.
#> 13 hd5 865.