Practical guides · Page 2
Search and filter all practical guidesChoose the Clustering Level for Robust Uncertainty
Align cluster-robust covariance estimation with shared disturbances and the number of independent groups.
Extract a Cluster-Trial Effect and Its Correct Uncertainty
Distinguish clusters, participants, and adjusted standard errors when adding a cluster-randomized study to a synthesis.
Recognize When Selection Can Create an Association
Audit inclusion rules and adjusted variables for common-effect structures.
Distinguish Uncertainty in a Mean from Variation in a Future Observation
Choose an interval that matches whether the target is a population mean or a new individual measurement.
Check the Functional Form of a Continuous Predictor
Evaluate whether a straight-line contribution is plausible without replacing continuous information with arbitrary categories.
Extract Crossover Results Without Losing the Pairing
Identify sequence, period, and within-person information before treating crossover trial outcomes as independent groups.
Check CSV Delimiters and Quoting Before Counting Records
Distinguish logical records from physical lines and prevent embedded punctuation from shifting columns.
Turn a Causal Diagram Into an Auditable Adjustment Plan
State the causal assumptions and target effect before accepting a software-generated adjustment set.
Import Decimal Commas Without Changing Numeric Meaning
Specify decimal and thousands separators explicitly and test values that distinguish competing interpretations.
Compare Net Benefit at Clinically Meaningful Thresholds
Translate classification counts into a decision comparison while stating the threshold’s tradeoff.
Adjudicate Duplicate Observations Before Dropping Rows
Separate repeated data entry from legitimate repeat measurements and make the retained-record rule auditable.
Link Multiple Reports Without Merging Different Studies
Use a study-family evidence table to prevent duplicate participant counts and preserve uncertain matches.