Publications by George
Multidim IRT - Spanish Production
Multi-dimensional IRT Models Here we attempt to determine whether the latent space of the data is multidimensional via exploratory multi-factor models. We fit exploratory 2- through 8-factor 2PL models, and then compare them. Below is a table showing sequential model comparisons from the ordinary 2PL up to the 8-factor exploratory model. AIC cont...
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CDI-CAT Validation
Load the things Data were collected from 250 participants, 47 of whom were excluded based on our preregistered criteria (mismatched demographic data, low birthweight, or developmental delays). An additional 0 participants met our strict exclusion criterion of disagreement on at least 75% of their CAT vs. full CDI responses, but several other pa...
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Curiobaby Drop Exp 2 Analysis
## Loading required package: here ## here() starts at /Users/gkacherg/Documents/GitHub/curiobaby_drop ## Loading required package: tidyverse ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ── ## ✓ ggplot2 3.3.2 ✓ purrr ...
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Input Distributions
Data What do the overall adult word count (AWC) per minute look like for different children? Is there greater consistency within- than between-children? d’Apice, Latham, & von Stumm (2019) found that daily home language input varied as much within- as between families (intraclass correlation = .47), but this was computed on the daily totals per...
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Wordbank IRT Analysis
Let’s take a step back from implementing bespoke Stan code for the full Standard Model, with real, unscaled units for input rate, word frequency and difficulty. This was troublesome due to convergence issues in our preferred model which seems to imply issues with identifiability (see also discussion in Buerkner, 2017: unless you have fixed scal...
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Curiodrop model analysis
Preprocessing Load human data And define helper functions ## `summarise()` has grouped output by 'relation', 'drop'. You can override using the `.groups` argument. ## `summarise()` has grouped output by 'relation', 'drop'. You can override using the `.groups` argument. Fit models to all trials (MSE objective) Find best-fitting betas per feature...
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Peekbank Time Window Analysis
Motivation Peelle and Van Engen (2020) style multiverse analysis considering possible time windows with logistic growth curve models in a dataset with words of varying frequency, stimuli with varying levels of noise, and with young or old adults. For our analysis, we will restrict ourselves to familiar words, and will model age effects. # get loc...
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DLL Word List Evaluation, v2
Goals The goals are 1) to create a word list that is informative about both English and Spanish vocabulary size and 2) to ensure that there are sufficient doublets to estimate lexical overlap. On an IRT view, we can’t perfectly assess 2 (at least not without better bilingual CDI data), but we can assess criterion 1 - that is, we can look at whe...
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Exploratory Multidim IRT - English
Multi-dimensional IRT Models Here we attempt to determine whether the latent space of the data is multidimensional via exploratory multi-factor models. We fit exploratory 2- through 8-factor 2PL models, and then compare them. ## `summarise()` regrouping output by 'definition', 'lexical_class' (override with `.groups` argument) Below is a table sh...
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DLL Word List Evaluation, v3
Goals The goals are 1) to create a word list that is informative about both English and Spanish vocabulary size and 2) to ensure that there are sufficient doublets to estimate lexical overlap. On an IRT view, we can’t perfectly assess 2 (at least not without better bilingual CDI data), but we can assess criterion 1 - that is, we can look at whe...
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