<p>A random effects test of the models versus a baseline model was performed by simulating random expected value estimates (10,000 repetitions) and then computing a non-parametric p-value per subject as the fraction of repetitions in which the baseline BIC is lower than the model BIC (indicating a better fit). These p-values were then combined across subjects using Fisher's combined probability test. Only HMM outperforms the baseline model in both the appetitive and aversive sessions.</p
I Random effects meta-analysis often conducted in two stages: xi ∼ N(θi, s2i) from each study i θi ∼...
<p>LME-RSI: a linear mixed-effects model with random slope and intercept; LME-RI: a linear mixed-eff...
Three nested models are compared in their ability to reproduce the pattern of interest observed in a...
Linear regression analysis is important in many fields. In the analysis of simulation results, a reg...
<p>A) The predicted response was compared to the observed responses from which a coefficient of dete...
<p>These models have frequencies and . These frequencies refer to the population from which the sub...
<p>(top) Posterior model probability (see color bar) for each subject. For an exact description of e...
Background: The theory has been put forward that if a null hypothesis is true, P-values should follo...
This paper proves that it is wrong to require that regressing a model's outputs on the observed real...
BACKGROUND: The theory has been put forward that if a null hypothesis is true, P-values should follo...
This paper argues that it is wrong to require that regressing the outputs of a trace-driven simulati...
<p>*Values are significantly different from random prediction (One-Sample t-test, p < 0.01, One-Samp...
<p>(top) Posterior model probability (see color bar) for each subject. For the exact description of ...
The design of a randomized study guarantees not only clear and “in-terpretable comparisons”(Kinder a...
In single-case research, multiple-baseline (MB) design is the most widely used design in practical s...
I Random effects meta-analysis often conducted in two stages: xi ∼ N(θi, s2i) from each study i θi ∼...
<p>LME-RSI: a linear mixed-effects model with random slope and intercept; LME-RI: a linear mixed-eff...
Three nested models are compared in their ability to reproduce the pattern of interest observed in a...
Linear regression analysis is important in many fields. In the analysis of simulation results, a reg...
<p>A) The predicted response was compared to the observed responses from which a coefficient of dete...
<p>These models have frequencies and . These frequencies refer to the population from which the sub...
<p>(top) Posterior model probability (see color bar) for each subject. For an exact description of e...
Background: The theory has been put forward that if a null hypothesis is true, P-values should follo...
This paper proves that it is wrong to require that regressing a model's outputs on the observed real...
BACKGROUND: The theory has been put forward that if a null hypothesis is true, P-values should follo...
This paper argues that it is wrong to require that regressing the outputs of a trace-driven simulati...
<p>*Values are significantly different from random prediction (One-Sample t-test, p < 0.01, One-Samp...
<p>(top) Posterior model probability (see color bar) for each subject. For the exact description of ...
The design of a randomized study guarantees not only clear and “in-terpretable comparisons”(Kinder a...
In single-case research, multiple-baseline (MB) design is the most widely used design in practical s...
I Random effects meta-analysis often conducted in two stages: xi ∼ N(θi, s2i) from each study i θi ∼...
<p>LME-RSI: a linear mixed-effects model with random slope and intercept; LME-RI: a linear mixed-eff...
Three nested models are compared in their ability to reproduce the pattern of interest observed in a...