effect

Effect modifier like age stratification was compared with QTc prolongation.

Deciding which covariates would be effect modifiers based on the differences in trial results requires a careful analysis by first generating a potential list of potential effect modifiers for the treatments in question based on prior knowledge from literature.

Apart from the primary outcome, in the results we have stratified safety among the age and gender, to see effect modifiers. We found no statistically significant effect of age and gender on GB perforation and so as on safety of the intervention.

The association was stronger for subjects > 84 years of age (3.41%; 95% CI, 2.10-4.74) than for younger subjects, but age was not a significant effect modifier (p-REM = 0.270), and associations did not follow a monotonic trend with age.

For the meta-analysis of each effect modifier, cities with < 10 observations in a cell were excluded.

To further explore the heterogeneity in the observed city-specific exposure-response associations, we investigated several city descriptive variables as potential effect modifiers that could alter the shape of the curve.

For environmental health scientists interested in pursuing health effects research that incorporates genetic effect modifiers, we describe a framework for an investigation that includes polymorphisms.

Effect modifiers were controlled through stratification.

Bronchial Wash Gene Xpert for MTB results were cross tabulated with different effect modifiers such as gender, age, socio-economic status, educational status, duration of symptoms and ATT.

Effect modifiers and genders were controlled by stratification using Chisquare test.

Data were stratified for dose of steroids, age and gender to address the effect modifiers. Poststratification chi-square test was applied to check the significance with p-value < 0.05 as significant.

We then need to target both interventions and effect modifiers, such as social, community, and financial resources, that might buffer the effects of this negative stress."

Furthermore, participants were asked about (family) history of hypertension and cardiovascular disease (see Supplemental Material, "Confounders and effect modifiers," for a full list of covariates).

RVR was also stratified among age, viral load and gender to see their effect as these are potential effect modifiers.