Publications by Jens Roeser
Concurrent learning of adjacent and nonadjacent dependencies
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...
13309 sym 2 img 2 tbl
Modelling writing hesitations in text writing as finite mixture process
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...
9075 sym 11 img 6 tbl
Concurrent learning of adjacent and nonadjacent dependencies
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...
13599 sym 2 img 2 tbl
Model-evaluation quiz [answers]
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...
2930 sym 27 img
Model assumptions workshop
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...
10854 sym R (1809 sym/36 pcs) 10 img
Model evaluation
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...
8407 sym R (1781 sym/32 pcs) 44 img 9 tbl
Model-assumptions quiz [answers]
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...
2684 sym 28 img
Model assumptions workshop (with answers)
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 (...
12714 sym R (3197 sym/64 pcs) 15 img
Writing modality comparison
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...
16242 sym 1 img 6 tbl
Year 1 stats spin-off lecture
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...
7848 sym R (3994 sym/28 pcs) 26 img