Table 3.

Brief summary of four methods of obtaining risk ratios for binary outcomes.

Name of method	Type of method	Background literature	Some advantages	Some disadvantages	Example of use in the global health literature	Exposure	Binary Outcome
Log-binomial	Direct	Wacholder (1986) [35]	Easy to implement.	May not converge; may estimate individual-level probabilities (and/or the upper bound of their 95% confidence intervals) above 1.	Gibson et al. (2017) [37]	Mobile phone based intervention to improve immunization rates, in a cluster-randomized trial	Full immunization by 12 months of age.
Modified log-Poisson	Direct	Zou (2004) [16]	Easy to implement; almost always converges.	May estimate individual-level probabilities (and/or the upper bound of their 95% confidence intervals) above 1.	Chan et al. (2017) [38]	AIDS-related stigma	Probable depression (PHQ-9 score ≥10 or recent suicidal thoughts).
Substitution	Indirect	Zhang and Yu (1998) [25]	Easy to implement. Uses output from logistic regression.	Generally produces biased estimates and 95% confidence intervals are expected to be too narrow, on average [18].	Agweyu et al. (2018) [39]	Various demographics and health-related exposures	Mortality.
Marginal or Conditional Standardization	Indirect	Localio et al. (2007) [18]	Uses output from logistic regression.	May be more difficult to implement and interpret than other methods, especially in certain software packages.	Weobong et al. (2017) [40]	Psychological intervention for depression, in a randomized trial	Remission from depression as measured by the PHQ-9.

Abbreviation: PHQ-9 – Patient Health Questionnaire 9-item [36], a screening tool for depression.