Hypothesizing |
T1 |
R6 |
Conducting explorative research without any hypothesis |
T2 |
|
Studying a vague hypothesis that fails to specify the direction of the effect |
Design |
D1 |
A8 |
Creating multiple manipulated independent variables and conditions |
D2 |
A10 |
Measuring additional variables that can later be selected as covariates, independent variables, mediators, or moderators |
D3 |
A5 |
Measuring the same dependent variable in several alternative ways |
D4 |
A7 |
Measuring additional constructs that could potentially act as primary outcomes |
D5 |
A12 |
Measuring additional variables that enable later exclusion of participants from the analyses (e.g., awareness or manipulation checks) |
D6 |
|
Failing to conduct a well-founded power analysis |
D7 |
C4 |
Failing to specify the sampling plan and allowing for running (multiple) small studies |
Collection |
C1 |
|
Failing to randomly assign participants to conditions |
C2 |
|
Insufficient blinding of participants and/or experimenters |
C3 |
|
Correcting, coding, or discarding data during data collection in a non-blinded manner |
C4 |
D7 |
Determining the data collection stopping rule on the basis of desired results or intermediate significance testing |
Analyses |
A1 |
|
Choosing between different options of dealing with incomplete or missing data on ad hoc grounds |
A2 |
|
Specifying pre-processing of data (e.g., cleaning, normalization, smoothing, motion correction) in an ad hoc manner |
A3 |
|
Deciding how to deal with violations of statistical assumptions in an ad hoc manner |
A4 |
|
Deciding on how to deal with outliers in an ad hoc manner |
A5 |
D3 |
Selecting the dependent variable out of several alternative measures of the same construct |
A6 |
|
Trying out different ways to score the chosen primary dependent variable |
A7 |
D4 |
Selecting another construct as the primary outcome |
A8 |
D1 |
Selecting independent variables out of a set of manipulated independent variables |
A9 |
D1 |
Operationalizing manipulated independent variables in different ways (e.g., by discarding or combining levels of factors) |
A10 |
D2 |
Choosing to include different measured variables as covariates, independent variables, mediators, or moderators |
A11 |
|
Operationalizing non-manipulated independent variables in different ways |
A12 |
D5 |
Using alternative inclusion and exclusion criteria got selecting participants in analyses |
A13 |
|
Choosing between different statistical models |
A14 |
|
Choosing the estimation method, software package, and computation of SEs |
A15 |
|
Choosing inference criteria (e.g., Bayes factors, alpha level, sidedness of the test, corrections for multiple testing) |
Reporting |
R1 |
|
Failing to assure reproducibility (verifying the data collection and data analysis) |
R2 |
|
Failing to enable replication (re-running of the study) |
R3 |
|
Failing to mention, misrepresenting, or misidentifying the study preregistration |
R4 |
|
Failing to report so-called “failed studies” that were originally deemed relevant to the research question |
R5 |
|
Misreporting results and p-values |
R6 |
T1 |
Presenting exploratory analyses as confirmatory (HARKing) |