# Questions tagged [regression]

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

17,563 questions
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### What distribution to use to model changes in ratios?

I have some data corresponding to changes in a binomial variable - i.e, in month 1 there were n1 trials and k1 successes, and in month 2 there were n2 trials and k2 successes. Say I have M of these ...
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### Explain model adjustment, in plain English

Reading about methods and results of statistical analysis, especially in epidemiology, I very often hear about adjustment or controlling of the models. How would you explain, to a non-statistician, ...
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### Start time requirements or assumptions for survival analysis

We have prospective data from an observational registry and wish to consider the affects of a gene on time to cardiovascular events. The data includes standard data like age, gender, ... and also the ...
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### Adding coefficients to obtain interaction effects - can I add standard errors?

I posted this question earlier and am rewriting it in hopes of getting some guidance. I am using a weighted regression (after propensity score matching) to obtain estimates of the effects of a ...
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### Adding coefficients to obtain interaction effects - what to do with SEs?

I have a multivariate regression, which includes interactions. For example, to get the estimate of the treatment effect for the poorest quintile I need to add the coefficients from the treatment ...
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### How do I decide what span to use in LOESS regression in R?

I am running LOESS regression models in R, and I want to compare the outputs of 12 different models with varying sample sizes. I can describe the actual models in more details if it helps with ...
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### Regression specification choices

I am studying a population of individuals who all begin with a measureable score of interest (ranging from -2 to 2) [call it "old"], then they all undergo a change to a new score (also ranging from -2 ...
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### What algorithm is used in linear regression?

I usually hear about "ordinary least squares". Is that the most widely used algorithm used for linear regression? Are there reasons to use a different one?
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### Shall I trust AIC (non-full model) or slope (full model)?

The purpose to run regressions for butterfly richness again 5 environmental variables is to show the importance rank of the independent variables mainly by AIC. In non-full models, they reveal that ...
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### Method to compare variable coefficient in two regression models

I am regressing two butterfly richness variables (summer and winter) against a set of environmental variables separately. (variables with continuous numbers) Environmental variables are identitcal ...
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### If the t-test and the ANOVA for two groups are equivalent, why aren't their assumptions equivalent?

I'm sure I've got this completely wrapped round my head, but I just can't figure it out. The t-test compares two normal distributions using the Z distribution. That's why there's an assumption of ...
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### Regression coefficients that flip sign after including other predictors

Imagine You run a linear regression with four numeric predictors (IV1, ..., IV4) When only IV1 is included as a predictor the standardised beta is +.20 When you ...
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### What type of post-fit analysis of residuals do you use?

When carrying out OLS multiple linear regression, rather than plot the residuals against fitted values, I plot the (internal) Studentized residuals against fitted values (ditto for covariates). These ...
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### Coefficient of Determination ($r^2$): I have never fully grasped the interpretation

I want to fully grasp the notion of $r^2$ describing the amount of variation between variables. Every web explanation is a bit mechanical and obtuse. I want to "get" the concept, not just mechanically ...
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### Mixed regression models and custom link functions in R?

It seems like the current revision of lmer does not allow for custom link functions. If one needs to fit a logistic linear mixed effect model with a custom link function what options are available ...
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### What do ROC curves tell you that traditional inference wouldn't?

When would you tend to use ROC curves over some other tests to determine the predictive ability of some measurement on an outcome? When dealing with discrete outcomes (alive/dead, present/absent), ...
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### Is there an intuitive explanation why multicollinearity is a problem in linear regression?

The wiki discusses the problems that arise when multicollinearity is an issue in linear regression. The basic problem is multicollinearity results in unstable parameter estimates which makes it very ...
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### Regression-multiple observations per subject

I have data for about 1 year, 100 observations, multiple observations per subject, transactions occur on weekly basis but have 6-12 subjects per week, there is no order to this. There is a policy ...
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### Can I predict percentage change in earnings from percentage change in produced and percentage changed in price? [closed]

I have computed percentage change from time1 to time2 for several variables. Can I predict percentage change in earnings from percentage change in produced and percentage changed in price? When I ...