Summary: Arms

Read the summary and the most important questions on ARMS

• 1 Week 1

• 1.1 PowerPoint week 1

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• Frequentist framework: still mainstream

  
  
  
  
  

  • Test how well the data fit H0 (NHST)
    
  • p-values, confidence intervals, effect sizes, power analysis
    

• Bayesian framework: increasingly popular

  
  
  
  
  

  • Probability of the hypothesis given the data, taking prior information into account
    
  • Bayes factors (BFs), priors, posteriors, credible intervals
    

• Bayesian probability of a hypothesis being true depends on two criteria:

  
  
  
  
  

  1. How sensible it is, based on prior knowledge (the prior)
     
  2. How well it fits the new evidence (the data)
     

• Assumption: interval/ratio variables

  
  
  
  
  Example RQ: Are gender and age predictors of grade?
  o Grade on scale 0-10; numbers have numerical meaning: OK!
  o Age in years; numbers have numerical meaning: OK!
  o Gender coded as: 1 = male; 2 = female
  →Categorical; numbers do not have numerical meaning: Not OK!

• Evaluating the modelWith Bayesian statistics:

  
  
  o Estimate parameters of model
  o Compare support in data for different models/hypotheses using Bayes factors
  

• 1.2 Seminar 1

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• When would it have been selective reporting and why is that a problem?

  
  
  
  
  If you only report/discuss significant results (and not the total number of tests).
  Then, literature seems to only show that the effect is present; no evidence that the effect is not present.
  + publication bias (one aspect of it): only articles with significant effects are published. Problem: Literature also shows an effect when it is not there.

• Four central aspects of the registered reports model

  
  
  
  
  

  • Researchers decide hypotheses, study procedures, and main analyses before data collection.
    
  • Part of the peer review process takes place before studies are conducted.
    
  • Passing this stage of review virtually guarantees publication.
    
  • Both original studies and high-value replications are welcome.
    

• How registered reports work

  Authors submit STAGE 1 manuscript with Introduction, Proposed Methods & Analyses, and (if applicable) Pilot Data -> 
  Stage 1 peer review (Reviewers assess importance of research question and rigour of the methodology according to specific criteria)->
  
  If reviews are positive, then the journal offers in-principe acceptance (IPA), regardless of study outcome (protocol archived)

• Exploratory Reports article type

  • De-emphasis on a priori hypotheses and p values
    
  • Greater emphasis on parameter estimation and hypothesis generation; instead of hypothesis confirmation / evaluation
    

• 1.4.2 Assumptions

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• Which are the assumptions for MLR

  there are linear relationships between the dependent variable and each of the continuous independent variables.
  
  there are no outliers.
  
  absence of multicollinearity
  
  Homoscedasticity
  
  Normally distributed residuals