Publications by Jens Roeser

Detection theory in ecological biology

19.10.2021

Detection theory in ecological biology DaCosta & Sorenson (2014) Manubay & Powell (2020) Corral-López et al. (2017) Russell et al. (2020) Hemingway et al. (2019) Cole & Endler (2018) Caspers et al. (2017) ROC curves for all studies in overview References Jens Roeser Compiled Oct 27 2021 Detection theory in ecological biology DaCosta & Sore...

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Looking back in L2 text production

23.08.2021

Looking back in L2 text production 1 Brief summary 2 Data analysis 3 Text data 3.1 Sample 3.2 Length of production sequence 3.3 Editing frequency 3.4 Number of transitions 3.5 Productivity 4 Lookback during writing 4.1 Lookback probability 4.2 Number of fixation during lookback 4.3 Total-fixation duration of lookback 4.4 Transition duration o...

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Development of writing modalities

09.11.2021

1 Data analysis Data were analysed in Bayesian linear mixed effects models (Gelman et al. 2014; McElreath 2016). The R (R Core Team 2020) package brms (Bürkner 2017b, 2018) was used to model the data. Models were fitted with weakly informative priors (see McElreath 2016), and run with 10,000 iterations on 3 chains with a warm-up of 5,000 iterati...

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Concurrent learning of adjacent and nonadjacent dependencies

05.02.2022

1 Methods 1.1 Design All participants were exposed to adjacent and non-adjacent dependencies. In a sequence A-B-C, the location of a dot C was target of an adjacent dependency when always following the same B location while the location of dot A was random. In nonadjacent dependencies, the location of a dot C was always following the same locati...

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Data viz workshop

25.04.2022

Outline principles of data visualisation grammar of graphics aesthetics and attributes geometries major tools of data visualisation cosmetics What is data visualisation? graphical representation of data graphical data analysis (stats): what do we want to know? communication and perception (design): what do we want to communicate? exploratory p...

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Bahavioural stability clusters

27.05.2022

Principal component analysis Load data: data <- read_csv("../data/by_ppt_means_wide.csv") %>% select_if(~ !any(is.na(.))) # remove variables that contains NAs Run principal component analysis: # Principal component analysis pc <- prcomp(dplyr::select(data, where(is.double)), center = TRUE, scale = TRUE) Scree plot suggests 6 or 7 PCs. These a...

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Data wrangling workshop

25.04.2022

About me: Jens Roeser early career researchfellow @ psychology department (Nottingham Trent University) theory: psycholinguistics; language production / comprehension / acquisition methods: Bayesian modelling (talk to me about mixture models, Roeser et al. 2021) in Stan; keystroke logging; eyetracking teaching: statistics – R of course (psyntu...

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Slides for R Markdown workshop

25.04.2022

R markdown combination of text, (R)code, and data documentation of all analysis steps (for us and our readers) quickly updating and repeating analysis communication of analysis / results producing texts, website, supplementary materials, walkthroughs, APA style manuscripts, slides easy cross referencing of tables and figures, citations automatic...

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