1. Unused methods.

Method	Approach
Measurement of treatment effects	Continuous data When studies use different scales, we will calculate the standardised mean difference (SMD) using Hedges' g, and present it with 95% confidence intervals. If some studies report an outcome as a dichotomous measure and others used a continuous measure of the same construct, we will convert the results for the former, the dichotomous measure, to a SMD.
Cluster‐randomised studies	For each included study, we will determine whether the unit of analysis is appropriate for the unit of randomisation and the design of that study (i.e. whether the number of observations match the number of randomised 'units' (Deeks 2011)). The presence of cluster‐randomised trials is unlikely because such a design is uncommon in this field. However, if we encounter such trials, we will use the intraclass correlation coefficient (ICC) to convert trials to their effective sample size before incorporating them into the meta‐analysis, as recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). If the ICC is not available, we will use values from the published literature as an external source, when available, as well as contacting the study authors and requesting them to supply more data to allow calculation of an ICC estimate (Campbell 2000). We will only use the ICC to calculate the effective sample size or the effective SD for those cluster‐randomised trials that do not account for the cluster effects. We will label such studies with a C.
Assessment of reporting bias	If there are more than 10 studies grouped in a comparison, we will evaluate whether reporting biases are present by using funnel plots to investigate any relationship between effect estimates and study size or precision, or both, as recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Sterne 2011). Due to the small number of studies expected, no formal test for plot asymmetry is planned.
Subgroup analysis and investigation of heterogeneity	Mode of delivery of baby (vaginal vs caesarean section). Short‐term and long‐term follow‐up (< 4 weeks vs ≥ 4 weeks of treatment). Low‐quality trials vs high‐quality trials (allocation concealment vs lack of allocation concealment; blinding vs lack of blinding).
Sensitivity analysis	We will conduct sensitivity analyses to determine whether findings are sensitive to the following: bias, by restricting the analyses to studies judged to be at low risk of bias for blinded assessment of the primary outcome; imputed data, by calculating the treatment effect including and excluding the imputed data to assess whether this alters the outcome of the analysis; dropouts and exclusions, by conducting worst‐case vs best‐case scenario analyses; the definition of colic used, by conducting analyses on studies using the stringent Wessel definition of infant colic (Wessel 1954), the more recent definition given by Hyman 2006, and a non‐recognised definition.