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## What is a parallel mediator?

In parallel mediation, **two or more variables (M1**. **, M2**. **, etc.)** **are proposed to mediate the relationship between X and**. **Y** (see Figure 2).

## What variables are selected to be mediators?

A mediator is a way in which an **independent variable** impacts a dependent variable. It’s part of the causal pathway of an effect, and it tells you how or why an effect takes place. If something is a mediator: It’s caused by the independent variable.

## Can you have two mediators?

As noted above, **when multiple mediators are of interest, the approach of considering mediators one at a time will only be appropriate if the mediators do not affect one another**. If one of the mediators of interest affects another then assumption (4) will be violated for one or more mediators.

## What is the difference between a mediator and a confounder?

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

## What is a serial mediator?

Serial mediation hypothesises **a causal chain linking of the mediators (anxiety, fatigue, depression), with a specified direction flow**. For example, pain could increase anxiety, which in turn increases depression which could in turn increase fatigue and thus decrease QoL (ie, Pain->Anxiety->Depression-Fatigue->HRQoL).

## What is the difference between parallel and serial mediation?

**for parallel mediation, the causal relationship between both mediators should be zero or weak (some literature said).** **for serial mediation, the causal relationship between both mediators should be high**. Literature would decide what type of mediation test should adopt.

## How do you determine if a variable is a mediator?

A variable plays a role on the mediator variable under some specific conditions. The conditions of being the mediator variable are as follows: **If the change in the level of the independent variable significantly accounts for variation in the other variable, then the variable is considered a mediator variable**.

## What is mediator variables in research?

In communication research, a mediating variable is **a variable that links the independent and the dependent variables, and whose existence explains the relationship between the other two variables**. A mediating variable is also known as a mediator variable or an intervening variable.

## What are examples of mediators?

**When a couple is divorcing and they work with a neutral third party that helps them resolve divorce issues and divide up assets and property**, this is an example of mediation. Negotiation to resolve differences conducted by some impartial party.

## What is the difference between a mediator and a moderator?

**A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship**.

## What is a mediating variable example?

Mediator Variable Examples

For example, **suppose buying pizza for a work party leads to positive morale and to the work being done in half the time**. Pizza is the independent variable, Work speed is the dependent variable, The mediator, the middle man without which there would be no connection, is positive morale.

## What is the difference between a covariate and a mediator?

Mediators are part of the causal pathway from exposure to outcome. Moderators are interaction terms that change the size or direction (or both) of the effect of the exposure on outcome. **Covariates are other independent variables that may or may not predict outcomes**. A covariate may or may not be confounder.

## Is a mediator variable a covariate?

A mediating variable is a variable that translates fully or partially the effect of the main independent variable on the outcome. **A covariate is in my opinion unspecified and could refer to either of these.**

## What are covariates in mediation?

Covariate- **a variable that is related to X or Y or both**. The relation between X and Y does not appreciably change when adjusted for the covariate. Not a mediator, confounder, or collider. • Moderator-a variable where the relation of X to Y is different at different values of the moderator.

## What is the difference between mediating and moderating variables?

Mediators are possible explanations for a relationship between X and Y. Moderators affect the magnitude of the effect of X on Y. Another difference is in the relationship that **mediators and moderators have with the independent variable**. In theory, mediators result from the independent variable (i.e., X → M).

## What does mediation relationship mean?

Mediation is a little more straightforward in its naming convention. **A mediator mediates the relationship between the independent and dependent variables – explaining the reason for such a relationship to exist**. Another way to think about a mediator variable is that it carries an effect.

## Can a variable be both moderator and mediator?

**No, mediation and moderation are different concepts**. Moderation makes the relationship stronger or weaker. There might be relationship between dependent and independent variables even in the absence of moderator variable. In case of mediation, the presence of mediator is a must.

## How do you explain mediation?

Mediators **describe the how or why of a (typically well-established) relationship between two other variables** and are sometimes called intermediary variables since they often describe the process through which an effect occurs. This is also sometimes called an indirect effect.

## Why do we examine mediators?

Including mediators and moderators in your research **helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world**. They are important to consider when studying complex correlational or causal relationships.

## What is mediation analysis research?

Mediation analysis is **a statistical method used to quantify the causal sequence by which an antecedent variable causes a mediating variable that causes a dependent variable**.

## What is mediation in multiple regression?

Mediation is **a hypothesized causal chain in which one variable affects a second variable that, in turn,** **affects a third variable**. The intervening variable, M, is the mediator.

## What are the assumptions for mediation analysis?

These three assumptions—**control for exposure-outcome, mediator-outcome, and exposure-mediator confounding**—essentially amount to controlling for the variables C_{1}, C_{2}, and C_{3} in Figure 1, corresponding with exposure-outcome confounders, mediator-outcome confounders, and exposure-mediator confounders, respectively.

## Is regression a mediation analysis?

**A mediation analysis is comprised of three sets of regression**: X → Y, X → M, and X + M → Y. This post will show examples using R, but you can use any statistical software. They are just three regression analyses! Step 1.