Questions tagged [regression]

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

Filter by
Sorted by
Tagged with
-2
votes
1answer
829 views

How to use stata for linear regression

...
0
votes
1answer
622 views

Is it enough to check residuals versus predicted values when assessing linearity assumption in multiple regression?

Is it enough to check residuals versus predicted values to see if the linearity assumption in multiple linear regression is satisfied? Because for many predictors, you can't visualize the plot with ...
0
votes
1answer
2k views

Computing Mallows' Cp with SAS

I have a question about SAS: How do you get the parameter estimate for Mallows' Cp procedure in SAS?
2
votes
2answers
1k views

Assumptions needed for multiple linear regression [duplicate]

Are assumptions for multiple linear regression basically the same as simple linear regression? One has to check for linearity for each of the continuous predictors versus the outcome variable? If ...
1
vote
0answers
153 views

How to model the size of a trade area?

I would like to model the dimensions of the trade areas for a group of stores. I have geocoded sales data for each store, which I used to construct a convex hull using a GIS program. Essentially, I ...
31
votes
4answers
78k views

Choosing the best model from among different “best” models

How do you choose a model from among different models chosen by different methods (e.g. backwards or forwards selection)? Also what is a parsimonious model?
1
vote
1answer
1k views

Normalizing error variance scale

Imagine we have two sets of data m1 and m2. m1 components have the dimension of [m^2/s] and m2 components are measured in [cm^2/s]. e.g. ...
3
votes
1answer
1k views

Putting limits on estimated coefficient values

I recently came across an example of using eviews to put non-linear/convex limits on estimated coeficients on OLS. I could track down a link to a forum describing how this is done (here)... But I don'...
12
votes
2answers
8k views

Proper use and interpretation of zero-inflated gamma models

Background: I am a biostatistician presently wrestling with a dataset of cellular expression rates. The study exposed a host of cells, collected in groups from various donors, to certain peptides. ...
0
votes
1answer
691 views

Calculating linear regression from limited information

Disclaimer: this is directly related to a homework problem. The example I am giving is based off the homework problem (because I am more interested in how to solve it than in what the answer is). ...
4
votes
3answers
501 views

Mismatch between significant variables from logistic regression and tree splits in R

I'm studying a data set in R using both regression trees (tree and rpart functions) and logistic regression. I'm finding explanatory variables in the regression which are significant, but when I fit a ...
4
votes
3answers
654 views

Circular/elliptical tests for datasets with magnitude and direction

I am trying to analyse (using R) a set of r(theta) data to see if the magnitude (r) is dependent on direction (theta). I have looked at circular statistics but these only seem to deal with the ...
2
votes
1answer
216 views

How to know which variables are more important in a process? [closed]

I have a process with 15 effective variables. I could record 9 variables to study its effect on process. I am looking for an appropriate factor to estimate the value of effectiveness of each factor. I ...
172
votes
5answers
218k views

How exactly does one “control for other variables”?

Here is the article that motivated this question: Does impatience make us fat? I liked this article, and it nicely demonstrates the concept of “controlling for other variables” (IQ, career, income, ...
4
votes
1answer
334 views

What statistical test to use to examine effect of condition on states over time?

I need to know the types of tests I need to be thinking about for this stats project. I will then go and look up the specific tests you recommend. The data is from all 50 states for the years 1960-...
0
votes
1answer
5k views

How do you plot interaction effects in SAS? [closed]

I want to plot interaction between two variables in SAS. One is continuous and the other is binary.
3
votes
1answer
157 views

Differences in coefficients

Suppose I want to see whether $z$ is a confounder for a model with $y$ the outcome variable and $x$ the predictor. If I adjust for $z$, and the adjusted coefficient of $x$ changes versus the ...
87
votes
3answers
83k views

What is the lasso in regression analysis?

I'm looking for a non-technical definition of the lasso and what it is used for.
0
votes
1answer
331 views

How to develop intuition about parameter estimation in AR-GARCH model?

consider a typical ar-garch model: y = sum( bi*xi ) + epsilon, epsilon~garch(p,q) In such case a typical textbook says that we should first estimate all bi's ...
8
votes
2answers
1k views

How to explain linear mixed models to laypeople?

I need to explain the concept of linear mixed models in an article targeted at a mainstream audience. Is there a way of communicating the gist of the concept in a sentence or two?
7
votes
1answer
3k views

L1 regression versus L2 regression

I am trying to develop an intuition for why L1 regression is more expensive than L2 regression. Can somebody point me to some material that explains why this is the case
7
votes
2answers
4k views

General linear hypothesis test statistic: equivalence of two expressions

Assume a general linear model $y = X \beta + \epsilon$ with observations in an $n$-vector $y$, a $(n \times p)$-design matrix $X$ of rank $p$ for $p$ parameters in a $p$-vector $\beta$. A general ...
2
votes
0answers
162 views

Testing endogeneity against decision probability

I am working with a model where the literature suggests there is potential endogeneity between the dependent variable and the primary independent variable of interest (a binary treatment). However, ...
16
votes
4answers
2k views

Classic linear model - model selection

I have a classic linear model, with 5 possible regressors. They are uncorrelated with one another, and have quite low correlation with the response. I have arrived at a model where 3 of the regressors ...
12
votes
2answers
5k views

Should I run separate regressions for every community, or can community simply be a controlling variable in an aggregated model?

I am running an OLS model with a continuous asset index variable as the DV. My data is aggregated from three similar communities in close geographic proximity to one another. Despite this, I thought ...
2
votes
2answers
2k views

Equivalence of Poisson and Weibull PH regression in a survival setting

Suppose we have the following dataset that records individual survival times (dur) and a covariate z: ...
7
votes
2answers
29k views

How to test a logistic regression model developed on a training sample on the data left out using R?

I have the summary of a logistic regression output in R. I used training data to make the model. How do I test the logistic regression model developed on the training data on the data left out? My ...
7
votes
2answers
2k views

Difference between bias-variance dilemma and overfitting

I'm wondering what difference it makes whether we talk about bias-variance dilemma where fitting a regression line to the given dataset reduces bias and increases variance or whether we talk about ...
16
votes
2answers
29k views

Interpretation of incidence-rate ratios

So, I want to fit a random effects negative-binomial model. For such a model STATA can produce exponentiated coefficients. According to the help file such coefficients can be interpreted as incidence-...
1
vote
1answer
3k views

When can I suppress the intercept using treatreg?

Can I suppress the intercept if I know the treatment will be zero if the independent variables are zero. Also, can I suppress the intercept if I know the right hand side of the primary regression ...
8
votes
1answer
6k views

How to specify Bayesian mixed effects model in BUGS

I posted this earlier in the week then retracted the question when I found a good source, not wanting to waste people's time. I haven't made much progress I'm afraid. In trying to be a good citizen ...
12
votes
2answers
10k views

Difference between t-test and ANOVA in linear regression

I wonder what differences are between t-test and ANOVA in linear regression? Is a t-test to test whether any one of the slopes and intercept has mean zero, while ANOVA to test whether all slopes have ...
2
votes
1answer
172 views

How do I transform a data generation specification in R into a BUGS/JAGS specification

I am at a loss about what the BUGS/JAGS specification of the following should look like. The background is that one person has four measurements taken by four different instruments. Each instrument ...
6
votes
2answers
5k views

Which link function for a regression when Y is continuous between 0 and 1?

I've always used logistic regression when Y was categorical data 0 or 1. Now I have this dependent variable that is really a ratio/probability. That means it can be any number between 0 and 1. I ...
1
vote
1answer
2k views

Why would significance of F-value change in linear regression if you change the reference group?

For categorical predictors with k levels, it doesnt matter what you choose as your reference group. So why would the F-value significance change in the linear regression if you change the reference ...
4
votes
1answer
3k views

What distributions are for the slope and for the intercept in linear regression?

In linear regression from a dataset $\{ (x_i, y_i), i=1,\cdots,N \}$, I wonder what distributions are for the slope and for the intercept? In Excel output, t-tests are used to tell whether the slope ...
0
votes
0answers
55 views

Summation representation for multivariate regressions (or other time-saving techniques) [duplicate]

Possible Duplicate: Efficient online linear regression Is there a summation representation for multivariate regressions? For example, if I regress $y$ on $X$ instead of using $\hat \beta = (X'X)^...
1
vote
1answer
286 views

Can you still use the least significant difference test even if the F test is not significant?

Can you still used the least significant difference test even if the F test is not significant?
6
votes
1answer
1k views

How do I adjust standard errors in a research study in which the control group is constructed via matching with replacement?

I have a treatment sample of 200 firms. I'm using propensity score matching to pair each treatment observation with one control (sampling with replacement, in order to minimize bias associated with ...
2
votes
1answer
25k views

Interpreting percentage units regression

log(sales) = beta_0 + beta_1 * GDP The usual process of transforming a variable such as price into log(price) to measure an approximate percentage change means ...
4
votes
1answer
216 views

Does a huge difference in the number of observations in a dummy variable influence its regression result?

I'm currently working on my thesis where I performed a multiple linear regression. The analysis is basically about the impact of projects. Among other independent variables I have the dummy variable ...
6
votes
1answer
1k views

Weighted regression for categorical variables

I have been trying to use weighted regression on some data where there are three categorical variables with the lm(y ~ A*B*C) command in R. This was to try ...
3
votes
1answer
150 views

What rules should guide scaling variables to maximise interpretation, particularly within a regression context?

Context: In this previous question @adhesh asked about the benefits of coding a binary variable zero-one rather than one-two. I realised when I wrote this answer that I had quite a lot to say about ...
7
votes
4answers
434 views

Fitting data based on an unobserved variable

I have pairs (x, y) which I would like to regress (x independent, y dependent). Plotting them, I see distinct bands which can be attributed to a third variable. Unfortunately this variable cannot be ...
2
votes
0answers
42 views

How to control for firm survival and allow for different firm types to emerge?

I'm doing program evaluation. I want to use the finite mixture model to test the hypothesis that different types of firms may exist. This is an endogenous determination of the number of different ...
9
votes
2answers
610 views

Which type of regression to use, considering one variable with upper bound?

I'm not sure which method to use to model the relationship between two variables ($x$ and $y$) in the experiment described as follows: There are 3 variables: $x_{aim}$, $x$ and $y$. The value of $x_{...
1
vote
2answers
4k views

Multiple linear regression on a data set with Python?

I'll preface my question with the fact that I'm just learning about linear regression so I may be thinking about this wrong. I have a set of data. In this set I have one dependent variable and about ...
1
vote
2answers
538 views

How to interpret basic output from a regression analysis?

I have been trying to interpret the results below, but I am finding it difficult. I wonder if someone could help me. All answers highly appreciated. Number of obs = 30 F( 2, 27) = 19.73 Prob > ...
15
votes
3answers
17k views

What is the effect of dichotomising variables?

When dichotomising variables, what information is lost in the process? How does a dichotomisation help in the analyses?
2
votes
2answers
116 views

What type of regression analysis is best to model the relationship between self-efficacy and activity level over three time points?

I am conducting an orthopedic study to predict improvements in activity level (dependent variable) based on a type of self-efficacy scale (the independent variable). There are, however, other ...

1
453 454
455
456 457
467