Terminology • devMSMs

This vignette contains some key definitions for using the Data Requirements, Specifying Core Inputs, Recommended Preliminary Steps, and Workflows vignettes. A more thorough introduction to these concepts can be found in the forthcoming manuscript: [insert link].

Key Terminology

Summary of terminology used in *devMSMs*
Term	Definition
Exposure	Exposure or experience that constitutes the causal event of interest and is measured at at least two time points, with at least one time point occurring prior to the outcome.
Outcome	Any developmental construct measured at least once at a final outcome time point upon which the exposure is theorized to have causal effects.
Exposure Time Points	Time points in development when the exposure was measured, at which weights formulas will be created.
Exposure Epochs	(optional) Further delineation of exposure time points into meaningful units of developmental time, each of which could encompass multiple exposure time points, that together constitute exposure main effects in the outcome model and exposure histories.
Exposure Histories	Sequences of relatively high (`'h'`) or low (`'l'`) levels of exposure at each exposure time point or exposure epoch.
Exposure Dosage	Total cumulative exposure epochs/time points during which an individual experienced high (or low) levels of exposure, across an entire exposure history.
Confounder	Pre-exposure variable that represents a common cause of exposure at a given time point and outcome; adjusting for all of which successfully blocks all backdoor paths.
Time-varying confounder	A confounder that often changes over time (even if it is not measured at every time point), and is affected by prior exposure, either directly or indirectly.
Time invariant confounder	A confounder that occurs only at a single time point, prior to the exposure and remains stable and/or is not possibly affected by exposure.
Collider	A variable that represents a common effect of exposure at a given time point and outcome; adjusting for which introduces bias.

Weights Formula

Weights formula are formula created at each exposure time point, regressing exposure on confounders, for the purpose of creating and/or assessing balancing weights. The general form is given by:

ESETA1.t ~ time-invariant confounders + time-varying confounders + lagged exposures + lagged outcomes

Below is a table that summarizes the three formula type’s that will be used.

Table 2.

Summary of the formula terminology used in the *devMSMs* package for creating balancing weights and assessing their performance in devMSMs (*Workflows* vignettes Steps 4-6). The different kinds of formulas vary with respect to their inclusion of time-varying confounders and the `type` specification to create them using the `createFormulas()` function.
Term	Definition
Full balancing formula `type = "full"`	Balancing formula containing all time invariant, all lagged time-varying confounders, and lagged exposure values. Used for pre-balance (Workflows vignettes Step 4b) and final balance assessment (Workflows vignettes Step 6). `ESETA1.24 ~ B18Raw.15 + B18Raw.6 + BioDadInHH2 + CORTB.15 + CORTB.6 + DrnkFreq + ES.15 + ES.6 + gov_assist + HOMEETA1.15 + HOMEETA1.6 + HomeOwnd ...`
Simplified balancing formula `type = "short"`	Balancing formula containing all time invariant, only t-1 lagged time-varying confounders, and lagged exposure values. Used for creating and assessing preliminary balancing weights to determine optimal weighting method (Workflows vignettes Step 5b). `ESETA1.24 ~ B18Raw.15 + BioDadInHH2 + CORTB.15 + DrnkFreq + ES.15 + gov_assist + HOMEETA1.15 + HomeOwnd ...`
Updated balancing formula `type = "update"`	Balancing formula containing all time invariant, only t-1 lagged time-varying confounders, as well as any imbalanced time-varying confounders, and lagged exposure levels at t-1+ Used to create final balancing weights (Workflows vignettes Step 6). `ESETA1.24 ~ B18Raw.15 + BioDadInHH2 + CORTB.15 + DrnkFreq + ES.6 + ES.15 + gov_assist + HOMEETA1.15 + HomeOwnd ...`

7 core functions of devMSMs

There are 7 key functions that are used in the devMSMs workflow.

Summary of the 7 core functions of the *devMSMs* package.
Function	Purpose	Required.Input	Output
`initMSM()`	Creates MSM object with core variables for use in all other functions.	`exposure`, `time invariant confounders`, `time-varying confounders`)	msmObject
`createFormulas()`	Creates balancing formulas at each exposure time point relating exposure to confounders.	`msmObject`, `type` (`'full'`, `'short'`, `'update'`)	List of balancing formulas for each exposure time point.
`assessBalance()`	Assesses confounder balance at each exposure time point according to best practices (Jackson, 2016).	`data`, `msmObject`	List of balance statistics. Tables & love plots displaying balance statistics at each exposure time point.
`createWeights()`	Creates balancing weights for each person (wrapper for `weightit::weightitMSM`).	`data`, `msmObject`	Weights object. Histogram & summary of balancing weights.
`trimWeights()`	Trims balancing weights to account for heavy tails.	`data`, `msmObject`	Trimmed weights object.Histogram & summary of trimmed weight.
`fitModel()`	Fits user-selected, weighted marginal model relating exposure to outcome.	`data`, `msmObject`, `weights`, `outcome`, `model` (`m0`-`m3`)	Fitted model object. Omnibus test & table of model evidence.
`compareHistories()`	Estimate, compare, & visualize model-predicted outcomes as a function of exposure history.	`data`, `msmObject`, `fitted model`	Tables of estimated values and comparisons. Boxplot.