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9 votes
Accepted

How do I understand ANCOVA in basic layman's terms?

To answer your question, I would like to invite you to think of a broader picture for, then, take you back to your original question. First, I would like to introduce a comparison between ANOVA and ...
8 votes

Between-subjects effect becomes non-signicant after centering covariate. Should I center or not?

Neither, or both, are correct. You often cannot interpret the main effect when you have an interaction in there. The main effect is the difference between the groups when the covariate is equal to ...
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8 votes

Student's t-test with a covariate?

One common means of controlling for some other covariate would be via regression. Put the X and Y values into the response (DV), and a Y-group indicator (0 if in X, 1 if in Y) as a DV, along with your ...
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8 votes
Accepted

Two-way ANOVA vs ANCOVA in R

Order matters whenever the predictors aren't independent. They're correlated in your first example, as they're continuous measurements on each of the diamonds, but not in the second, as those are ...
7 votes

Difference between two-way ANOVA, factorial ANOVA and ANCOVA: as analogies of linear regression

Compared to one way ANOVA: Two way ANOVA adds one more categorical independent variable to the regression (and possibly the interaction between the two IVs). Factorial ANOVA adds any number of ...
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6 votes
Accepted

Good data example needed with covariate affected by treatments

You may want to check out the mediation R package. It does include experimental data like jobs and ...
6 votes

Should covariates that are not statistically significant be 'kept in' when creating a model?

We really need more information about your goals to answer this question. Regressions are used for two main purposes: Prediction Inference Prediction is when your goal is to be able to guess at ...
6 votes
Accepted

The lines on my scatterplot for ANCOVA results doesn't look right, personal error or model error?

You appear to be misunderstanding the output from your model. In your code, the line: abline(fit.mice$coefficients[1:2], col="skyblue3") plots a line with the ...
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6 votes
Accepted

Difference between Repeated measures ANOVA, ANCOVA and Linear mixed effects model

First there is the question of whether it is OK to use percent change as the outcome. In a regression model with baseline as a regressor this is a very bad idea because the outcome is mathematically ...
  • 50.7k
6 votes

ANCOVA with all continuous variables

Instead of ANOVA use regression, which is the more general method: it's perfectly okay to do a regression with any mix of categorical and continuous variables. ANOVA is equivalent to a regression with ...
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5 votes
Accepted

Difference between a random slope/intercept model and an ANCOVA with an interaction?

In this case, I think you want to use the model with the interaction. A random slopes/intercepts model would suggest that you have slopes/intercepts that can vary with regard to some random factor. ...
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5 votes

Mixed-effect model / ANCOVA with lmer in R

No, your model is certainly wrong. A continuous variable can't be the grouping factor of a random effect. You need a random effect if the assumption of independence of residuals is violated. Typically ...
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5 votes

Fat tail? Short tail? Long tail? Where do I go from here?

Growth rates must be distributed as some variation of the Cauchy distribution. I have written a series of papers on this. The Cauchy distribution has no mean so it has no variance or covariance. ...
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5 votes
Accepted

Post-Hoc pairwise comparison for slope (interaction term) in R?

If you are using R to do the analysis, the emmeans package has an emtrends function that estimates estimated marginal slopes. e.g., ...
  • 16.7k
5 votes
Accepted

Two-Way ANCOVA: It is necessary to include a non-significant interaction term in the model?

It looks like other responses have already addressed the fact that there is no absolute rule that an interaction needs to be included. I'll just echo briefly that the decision of including an ...
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5 votes
Accepted

Can this be classified as an ANCOVA?

ANCOVA is terminology that some fields use to mean "linear regression with continuous and categorical variables". If Section is categorical and t is continuous, then I'd say this fits the ...
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5 votes

Justifying a smaller control group in survey study

I think you've answered your own question. If your goal is to independently assess the psychometric properties within the control group, collect enough data to do that. If your goal is only to compare ...
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4 votes

How to perform an ANCOVA in R

Here is a complementary documentation http://goo.gl/yxUZ1R of the procedure suggested by @Butorovich. In addition, my observation is that when the covariate is binary, using summary(lm.object) would ...
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4 votes

Good data example needed with covariate affected by treatments

I thought I'd show how an analysis comes out with one of the datasets in the mediation package. In framing, an experiment is done where subjects have the ...
  • 16.7k
4 votes

Student's t-test with a covariate?

By means of t-test you are assessing whether there is a significant difference between two sets of data --- e.g. the realizations of two random variables $X$ and $Y$. When using t-test you are doing a ...
4 votes

Do I have a justified reason to exclude a non-significant covariate from my ANCOVA? How interesting is unequal variance?

First, ask yourself why IQ is always included in such models. There is probably some reason. It might be that IQ is a mediator (see below) Second, from what you say, it sounds like IQ is a type of ...
  • 95.7k
4 votes
Accepted

Do I have a justified reason to exclude a non-significant covariate from my ANCOVA? How interesting is unequal variance?

First, let me assure you that - as mentioned by @amoeba - you are on the right path to land in "research hell", that is the place where researchers (should) go when they let their p-value to decide ...
4 votes
Accepted

Can ANCOVA be used with a dichotomous dependent variable? If not, what have these authors done?

The authors are talking about odds, so I'd guess they used logistic regression with multiple covariables ("multivariable regression"). The terms "ANOVA" and "ANCOVA" do not make much sense in the ...
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4 votes

Fat tail? Short tail? Long tail? Where do I go from here?

Your Q-Q plot doesn't look like it has a fat tail. I'll show you how a fat tail looks like: Your tail is like a Victoria Secret's model compared to the above. I wish some of my model residuals had ...
  • 57.1k
4 votes

Two-Way ANCOVA: It is necessary to include a non-significant interaction term in the model?

There is nothing in statistical theory or practice which requires you to include any interaction, or any main effect for that matter. You include in your model the variables which your scientific ...
  • 16.8k
4 votes

Two-Way ANCOVA: It is necessary to include a non-significant interaction term in the model?

There are two different definitions or understandings of the term ANCOVA. The first and a broader one is "Any linear model containing continuous/scale predictors besides factors (categorical ...
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4 votes

Questions concerning visualizing model results with the R-package visreg

The paper by Patrick Breheny and Woodrow Burchett (the authors of visreg) discuss all the issues raised in your question. Before I go into the specific questions, ...
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4 votes
Accepted

GPower: Difference in Sample Size for ANCOVA vs. Repeated Measures ANOVA in clinical trials

This is a topic for seriously misunderstanding G*Power! Thank you for bringing this up. We thought the following was an explanation for the matter: "When calculating the sample size for "...
4 votes

ANCOVA vs linear mixed model in R, using different functions gives me different results

To summarise: You've discovered that different packages & functions may implement different methods, so you shouldn't expect to get the same results when you throw your data at a sundry collection ...
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3 votes
Accepted

When to create a control group with paired T test

I think what you are stating is directionally right. But, to clarify you can conduct a paired t test with your one single group and measure how they fare before and after the treatment. You can also ...
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