# Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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### How to test whether a regression coefficient is moderated by a grouping variable?

I have a regression done on two groups of the sample based on a moderating variable (say gender). I'm doing a simple test for the moderating effect by checking whether the significance of the ...
115 views

So... let's say I have data that look something like this... (as I look at it now, in the actual data the red line is about 20% shorter than the black (at the high end... but you get the idea) I've ...
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### Should quantitative predictors be transformed to be normally distributed?

I am always struggling with normality testing for quantitative predictors (no factors) and transforming them to normality. If I am running a GLMM and my predictors are really non-normal, should I ...
123 views

### How to combine 2 different observations to improve state estimates?

Context Let $\mathbf{x}_i \in \mathbb{R}^{100}$ and $\mathbf{z}_i \in \mathbb{R}^{20}$ be input vectors with the same corresponding target $\mathbf{y}_i \in \mathbb{R}^{25}$. Using ridge regression we ...
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### Formula for weighted simple linear regression

This wiki page Simple linear regression has formulas to calculate $\alpha$ and $\beta$. Could anyone tell me how to derive the formulas in weighted case?
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### Need to refine results of logarithmic regression

Using a logarithmic regression tool found at xuru.org ( http://www.xuru.org/rt/LnR.asp#CopyPaste ) and the data from below, the curve of the graph for this data is roughly described by y = 31....
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### How to model bounded target variable?

I have 5 variables and I'm trying to predict my target variable which must be within the range 0 to 70. How do I use this piece of information to model my target better?
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### How to present a empirical study when using econometric models?

I've got a (probably easy) question in how to handle empirical studies, when there are a lot of effects involved. I have a whole bunch of variables and I'd like to analyze just a few of them. But the ...
7k views

### Mediation model with linear regression

In my master thesis I have drawn a few hypotheses. I have answered them all with linear regression. In these linear regressions, I took control variables into account. My question is: do I have to ...
170 views

### Interpreting a lots of effects

Does anybody know how to interpret a whole bunch of effects (main and interaction) in a clever way? Or does anybody have a good example where it's shown? To be more precisely: Assume that you have a ...
5k views

### Explanatory power of a variable

I have simple linear regression model. What I want to calculate is how "important" each of my input variables are i.e. to make a statement something like this: "60% of predictive power in this model ...
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### Interpretation lin-log regression where the covariate is log(x1 + 1) transformed

I have a lin-log regression model like $$Y = b_0 + b_1 \log(x_1 + 1) + e.$$ The distribution of $x_1$ is very skewed, thus I use the natural logarithm to get a more Gaussian like distribution. ...
391 views

### How to optimize the k parameters in dynamic linear regression?

I am starting to use R's dynlm package. Currently I am just looking at the fit and eyeball which choice of lags might be the best. Is there a standard way or a strategy to determine the best k ...
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### Persistence in time series

Could someone tell me what the term 'persistence' mean in time series analysis? It's regarding econometrics and applied regression.
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### Covariates in regression models

Should covariates be included in regression analyses if they are correlated with the dependent variable or if they are correlated with the predictor variable/s. Alternatively, should they be included ...
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### Fitting a beta-binomial model in the case of overdispersion in R

I'm estimating some count data. I have counts for say $m=100$ individuals. Unfortunately when using the Poisson regression overdispersion occurs. So I was thinking to fit a negbin model. But this is ...
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### Updating linear regression efficiently when adding observations and/or predictors in R

I would be interested in finding ways in R for efficiently updating a linear model when an observation or a predictor is added. biglm has an updating capability when adding observations, but my data ...
718 views

### What count-data models to choose besides negative binomial model when overdispersion occurs?

Assume that you have a Poisson model with overdispersion. Besides negative binomial models, what are other appropriate count-data modeling regression techniques?
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### Take the log of an independent variable in a Poisson regression

Is it possible to take the log of an independent variable in a Poisson regression? What to I have to be aware of, when doing so? (The results are getting better, when assuming that the independent ...
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### Why does noisy data result in better prediction performance?

I have tested a regression framework's robustness to noise and I have noticed in some cases that adding noise improves the prediction performance and in other cases the performance degrades. What ...
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### Interpret t-values when not assuming normal distribution of the error term

Assume that you have a regression with a whole set of variables and you know that the residuals are not normal distributed. So you just estimate a regression using OLS to find the best linear fit. For ...