Publications by Jens Roeser

Concurrent learning of adjacent and nonadjacent dependencies

12.11.2022

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 B was target of an adjacent dependency when always following the same A location while the location of dot C was random. In nonadjacent dependencies, the location of a dot C was always following a location A do...

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Modelling writing hesitations in text writing as finite mixture process

28.11.2022

1 Analysis 2 CATO 2.1 Data processing 2.2 Model comparisons 2.3 Posterior parameter estimates of mixture model 3 SPL2 3.1 Methods 3.2 Data processing 3.3 Model comparisons 3.4 Posterior parameter estimates of mixture model 4 PLanTra 4.1 Methods 4.2 Data processing 4.3 Model comparisons 4.4 Posterior parameter estimates of mixture model 5 LI...

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Concurrent learning of adjacent and nonadjacent dependencies

05.12.2022

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 B was target of an adjacent dependency when always following the same A location while the location of dot C was random. In nonadjacent dependencies, the location of a dot C was always following a location A do...

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Model-evaluation quiz [answers]

22.02.2021

Week 15: Model-evaluation quiz [answers] Week 15: Model-evaluation quiz [answers] Part 1 (1): assumptions and statistical modelling Part 1 (2): residuals and normality Part 2: independence of residuals Part 3: quiz evaluation Jens Roeser Compiled 2022-02-21 A total of 12 students completed this quiz (status: 2022-02-21 09:17:32). The correc...

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Model assumptions workshop

18.02.2021

Workshop 17 [Week 7]: Model assumptions Workshop 17 [Week 7]: Model assumptions Lecture review Learning outcomes Setup The normal distribution The area under the curve Central limit theorem Summary References Jens Roeser Compiled 2021-02-18 Lecture review Parametric models (t-test, ANOVA, linear regression) make assumptions about their inp...

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Model evaluation

15.02.2021

Model evaluation and violations Dr Jens Roeser Learning outcomes After completing this lecture, the workshop and your own reading you should be able to … explain what residuals are. run regression models with categorical predictors. evaluate statistical models on the basis of their unexplained (residual) variance. Model evaluation “Model...

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Model-assumptions quiz [answers]

17.02.2021

Week 14: Model-assumptions quiz [answers] Week 14: Model-assumptions quiz [answers] Part 1: Models and parametric tests Part 2: Properties of the normal distribution Part 3: CLT Part 4: iid Part 5: quiz evaluation Jens Roeser Compiled 2022-02-21 A total of 31 students completed this quiz (status: 2022-02-21 09:18:26). The correct answers ar...

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Model assumptions workshop (with answers)

18.02.2021

Workshop 17 [Week 7]: Model assumptions Workshop 17 [Week 7]: Model assumptions Lecture review Learning outcomes Setup Normal distribution The area under the curve Central limit theorem Summary References Jens Roeser Compiled 2021-02-18 Lecture review Parametric models (t-test, ANOVA, linear regression) make assumptions about their input (...

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Writing modality comparison

22.03.2021

1 Results 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 using the probabilistic programming language Stan (Carpenter et al. 2016; Hoffman and Gelman 2014). Models were fitted with weakly informative priors (se...

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Year 1 stats spin-off lecture

10.03.2021

Year 1 stats spin-off Dr Jens Roeser Learning outcomes After completing this lecture and the workshop you should have had the opportunity to … revisiting inferential statistics covered during year 1 statistics. practice your understanding of inferential statistics in a quiz (people may call this a mock exam). use an app to explore the relati...

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