Publications by George
Ggplot2 notes part 2
Here is part 2 of my guide to using ggplot2. Scales Following on directly from the previous notes you can manually adjust the colours and shapes used in the chart if you don’t like the defaults, as shown in figure 1. … Continue reading → Related To leave a comment for the author, please follow the link and comment on their bl...
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Using R.Net in an Excel Add in
I thought I’d try out R.net and in doing so I have put together a very simple Excel 2007 add in that connects Excel to R. I’m using .Net 4.0 in Visual Studio 2010 pro with the latest commit of R.Net, … Continue reading → Related To leave a comment for the author, please follow the link and comment on their blog: Sharp Stat...
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Multiple Binomial Tests
How many times will 1 or more of 12 binomial tests on data from 40 participants come out significant by chance? (In other words, is the false positive rate inflated by running a large number of binomial tests.) We will run a large number of simulated experiments with random binomial data (prob=.5), and measure 1) in what proportion of experiments...
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Bounding Boxes
Load Data Detections by type: load(here("data/all_bounding_boxes.RData")) #summary(df) table(df$label) ## ## face hand pose ## 8634190 16485085 22508789 Filter Weird Data We’ll also get rid of detections in videos that were not named with the standard format (and therefore we could not extract age from; e.g. 161384-Baby_Scene v...
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CDI-CAT English production (12-36 months)
Introduction Our primary goal here is to develop and test via simulation a bank of CDI items and IRT parameters that we can recommend to those wanting to develop and conduct CDI computerized adaptive tests (CATs). Our approach is as follows: We first fit basic IRT models (Rasch, 2PL, 3PL, 4PL) to the wordbank CDI English Words & Sentences form da...
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child-relevant scenes
Introduction Our goal is to start to get a handle on the variability and consistency of children’s everyday scenes and activity contexts, combining both the existing SAYcam annotations and analysis of the 397 scenes identified in the SUN dataset (used subsequently in the Places Database (Zhou et al. 2017)). How did the SUN dataset build a some...
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Adaptive CDI:WG Comprehension Test
Introduction Our goal here is to develop and test via simulation a bank of CDI:WG items and IRT parameters that we can recommend to those wanting to develop and conduct computerized adaptive tests (CATs) of children’s early word learning. This is to complement the CDI:WS item bank and parameters, and to be used by parents of children who are no...
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Adaptive CDI pruned Rasch model
Introduction Instead of using the Rasch parameters on the full set of CDI:WS items for CAT, we now first prune the set of items based on the 2PL fits. Data We use the English Words & Sentences CDI production data from wordbank, which includes a total of 5561 children. Examine Rasch Item Fits In our other CAT simulations we used the 2PL model, b...
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Adaptive CDI with Rasch Model
Introduction Our primary goal here is to develop and test via simulation a bank of CDI items and IRT parameters that we can recommend to those wanting to develop and conduct CDI computerized adaptive tests (CATs). For the Rasch model, we use the (full) item bank in a variety of computerized adaptive test (CAT) simulations on wordbank data, to be ...
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IRT analysis of wordbank for CATs
Introduction Our primary goal here is to develop and test via simulation a bank of CDI items and IRT parameters that we can recommend to those wanting to develop and conduct CDI computerized adaptive tests (CATs). Our approach is as follows: We first fit basic IRT models (Rasch, 2PL, 3PL, 4PL) to the wordbank CDI English Words & Sentences form da...
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