scholarly journals A comprehensive treatment of quadratic-form-based inference in repeated measures designs under diverse asymptotics

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Paavo Sattler
Keyword(s):  
Quadratic Form ◽  
Repeated Measures ◽  
Comprehensive Treatment ◽  
Repeated Measures Designs

Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments

2021 ◽  
pp. 1-18
Author(s):  
SCOTT CLIFFORD ◽  
GEOFFREY SHEAGLEY ◽  
SPENCER PISTON
Keyword(s):  
Treatment Effect ◽  
Repeated Measures ◽  
Treatment Effects ◽  
Repeated Measurements ◽  
Experimental Designs ◽  
Treatment Effect Size ◽  
Standard Design ◽  
Survey Experiments ◽  
Repeated Measures Designs ◽  
Alternative Designs

The use of survey experiments has surged in political science. The most common design is the between-subjects design in which the outcome is only measured posttreatment. This design relies heavily on recruiting a large number of subjects to precisely estimate treatment effects. Alternative designs that involve repeated measurements of the dependent variable promise greater precision, but they are rarely used out of fears that these designs will yield different results than a standard design (e.g., due to consistency pressures). Across six studies, we assess this conventional wisdom by testing experimental designs against each other. Contrary to common fears, repeated measures designs tend to yield the same results as more common designs while substantially increasing precision. These designs also offer new insights into treatment effect size and heterogeneity. We conclude by encouraging researchers to adopt repeated measures designs and providing guidelines for when and how to use them.

A Correction for the ε̃ Approximate Test in Repeated Measures Designs With Two or More Independent Groups

1991 ◽  
Vol 16 (4) ◽  
pp. 371-372 ◽  
Author(s):  
Bruno Lecoutre
Keyword(s):  
Repeated Measures ◽  
Test Procedure ◽  
Repeated Measures Designs

The routine ε̃ approximate test procedure in repeated measures designs when the condition of circularity is not fulfilled uses an erroneous formula in the case of two or more groups. This may lead to a substantial underestimation of the deviation from circularity when the total number of subjects is small.

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