MaldonadoCulbertson2022: experimental results (generated) #
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Experiment 2: English-speaking participants learned an artificial pronoun system with three plural forms for four plural person categories, first exclusive, inclusive, second and third, the inclusive sharing its form with the first exclusive (First-inclusive), the second (Second-inclusive) or the third person (Third-inclusive), between subjects. Accuracy in the second testing block was analysed by logistic mixed-effects models with treatment coding, first with First-inclusive and then with Second-inclusive as the baseline; the intercept compares the baseline's accuracy with chance.
Raw data #
- https://osf.io/p2c4r/: materials, data and analysis scripts of the three experiments
References #
The person whose plural form the inclusive shares.
- firstInclusive : Condition
First-inclusive: the inclusive shares the first person exclusive plural form
- secondInclusive : Condition
Second-inclusive: the inclusive shares the second person plural form
- thirdInclusive : Condition
Third-inclusive: the inclusive shares the third person plural form
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- MaldonadoCulbertson2022.instDecidableEqCondition x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
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How a p-value is printed.
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- MaldonadoCulbertson2022.instDecidableEqBound x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
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A row of §3.3, p. 318: a coefficient of a treatment-coded model of accuracy in the second testing block, the intercept or the difference of a condition from the baseline.
- baseline : Condition
The baseline condition.
- condition : Option Condition
The condition compared with the baseline, none for the intercept.
- beta : Data.Experiments.Decimal
The coefficient.
- bound : Bound
How the p-value is printed.
The p-value.
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The 5 rows of §3.3, p. 318, in the paper's order; checked against the PDF text layer only.
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