t(11)=6.28; p=0.0001; power=0.99
t=0.36; p=0.36; Z CC=0.38; 95% confidence interval=-0.215-0.959; mean +- SD delta near far congruent controls=2.59 +- 1.58; delta near far congruent P+ patient=3.19
t=-2.27; p=0.02; Z CC=-2.36; 95% confidence interval=-3.482-1.227; mean +- SD delta near far congruent controls=2.59 +- 1.58; delta near far incongruent P+ patient=-1.15

Examining the Testing Effect in University Teaching: Retrievability and Question Format Matter

equal distributions of participants across review

p=0.61, SE=0.04 compared Criterial Test 1
p=0.62, SE=0.05 compared Criterial Test 1

Using Card Sorting to Explore the Mental Representation of Energy Transition Pathways Among Laypeople

Alexithymia Predicts Attrition and Outcome in Weight-Loss Obesity Treatment

Impact of Emotional Harassment on Firm's Value

Gender Stereotypes in a Children's Television Program: Effects on Girls' and Boys' Stereotype Endorsement, Math Performance, Motivational Dispositions, and Attitudes

Individual Differences in Vicarious Pain Perception Linked to Heightened Socially Elicited Emotional States

test wise bonferroni confidence interval

How Do Men and Women Perceive a High-Stakes Test Situation?

Metacognitive Therapy Versus Cognitive Behavioral Therapy:A Network Approach

Advance Care Planning in Nursing Homes - Improving the Communication Among Patient, Family, and Staff: Results From a Cluster Randomized Controlled Trial (COSMOS)

Leaders' Gender, Perceived Abusive Supervision and Health

Emotional 'Patient-Oriented' Support in Young Patients With I-II Stage Breast Cancer: Pilot Study

The Influence of Teaching Approach on Students' Conceptual Learning in Physics

Repeating Numbers Reduces Results: Violations of the Identity Axiom in Mental Arithmetic

9 outcomes*2 problem types 4 repetitions=72 trials; 9 single numbers*4 repetitions=36

A Comparative Study on the Performance of GSCA and CSA in Parameter Recovery for Structural Equation Models With Ordinal Observed Variables

confidence interval of parameter estimates
ml estimator produces parameter estimates
csa ml can yield remarkably erroneous parameter estimates
vectorized elements of sample statistics
root mean squared error of parameter estimates
non convergence issues of csa based model