Tagged Questions

1
vote
0answers
35 views

How do I set up a multivariate hierarchical multiple linear regression in R?

I have two continuous DVs (measurements taken on individual fish), one continuous individual level IV (fish's size), and two site-level IVs (PC1 and PC4). Sites are either take or no take. There are ...
-1
votes
0answers
37 views

How to interpret the results of stepwise multiple regression with multiple subscales in for one measure

My hypotheses for were based on the stepwise regression in which the predictors were constructs measured by four separate measures. Three of the measures have subscales. Since each subscale is put ...
0
votes
0answers
26 views

Two IVs (schools) and 3 IVs (grade levels in each) where there are 2 DVs (math and reading scores)

Is MANOVA the correct test? I am looking at 3 grade levels in each of the two middle schools. I want to compare the standardized scores (reading and math) of students in each grade level to the same ...
3
votes
1answer
62 views

Errors in Variables and Deming's multivariate regression: Assumptions

There has been extensive literature that puts forth a standard set of assumptions for the Ordinary Least Squares (OLS) estimator. I am very interested in working around the two classical problems of ...
0
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3answers
343 views

Automatic outlier detection in R

Our model processes millions of multivariate observations; manual outlier detection is impractical. I am looking for a method of automatic outlier detection. I have been trying to use R package ...
0
votes
2answers
879 views

How to do multiple regression with limited experience and (hopefully) excel?

I am doing a study of how legal need relates to a number of predictors. Outcome Variable: Legal Need (Yes or No) Possible Predictors: Age, Gender, Race, Ethnicity, Language, Clinic, Insurance ...
6
votes
2answers
318 views

How do I analyse data with 2 independent variables and 2 dependent variables?

Im confused about what to do. I was thinking of running two seperate multiple regressions with a DV in each.. its after this, that I'm stuck. How do I see what effect the two DV's have combined? Or am ...
4
votes
1answer
349 views

Between / Within-Subjects Analysis (with multiple dependent variables): Multi level expert around?

I have the following experimental data and desperately lack expert advice: Of a total of 60 Subjects, 20 are randomly assigned to one of three conditions (1X3) during treatment Each subject ...
1
vote
1answer
459 views

How to create a composite variable to use as a response variable?

I am a student doing my master's thesis and I have a question regarding my study. I am working with country data for 25 countries and I am looking into cultural values, attitudes and ...
4
votes
0answers
100 views

Relationship between LASSO T and LARS number of steps k

We can see on the figure (cf Least Angle Regression p30, Efron, Hastie, Johnstone, Tibshirani - link: Least Angle Regression) that there is a direct relationship between: LASSO T absolute norm of ...
1
vote
1answer
684 views

Simple Multivariate Regression with Octave

For the last 2 months, I've been trying to do any kind of multivariate regression, but I haven't had much luck. I hear Octave is simpler and more intuitive for these kinds of tasks, so I thought I'd ...
3
votes
1answer
151 views

How can you relate the coefficients of a multivariate regression of ${\bf Y} \sim {\bf X}$ to the coefficients of ${\bf X} \sim {\bf Y}$?

Is anyone aware of a orthogonal multiple regression library that is implemented in say R, Scipy, Matlab, Octave, etc.? (Or even fortran/C...) If I'm not mistaken, it would not be difficult to write ...
9
votes
1answer
204 views

Is there a generalization of Pillai trace and the Hotelling-Lawley trace?

In the setting of multivariate multiple regression (vector regressor and regressand), the four major tests for the general hypothesis (Wilk's Lambda, Pillai-Bartlett, Hotelling-Lawley, and Roy's ...
0
votes
1answer
153 views

Which statistical test should I use when there are multiple latent predictors and multiple latent outcomes?

I am doing my research on Personality (the big five factors) and if personality can predict commitment to an organization. However, commitment is composed of three dimensions. What is the best ...
5
votes
1answer
132 views

How to compare weighted multivariate linear models?

I've got a set of multivariate regression models, with weights, that I'm trying to compare in R. Looks like: ...
5
votes
4answers
1k views

Reducing the number of variables in a multiple regression

I have a large data set consisting of the values of several hundred financial variables that could be used in a multiple regression to predict the behavior of an index fund over time. I would like to ...
0
votes
0answers
188 views

Confidence level for a multivariate linear regression

I am trying to use the Perl Statistics::Regression package to calculate a multivariate regression. The results I am getting per each of my variables are: Theta ...
13
votes
1answer
4k views

Multivariate multiple regression in R

I have 2 dependent variables (DVs) each of whose score may be influenced by the set of 7 independent variables (IVs). DVs are continuous, while the set of IVs consists of a mix of continuous and ...
4
votes
4answers
1k views

What should I be aware of when using multiple regression to find “causal” relationships in my data?

First of all, I realize multiple regression does not really give actually "causal" inferences about the data. Let me explain my current case: I have four independent variables which I hope (but am ...
5
votes
1answer
2k views

How to graphically compare predicted and actual values from multivariate regression in R?

I'm trying to write a function to graphically display predicted vs. actual relationships in a linear regression. What I have so far works well for linear models, but I'd like to extend it in a few ...
18
votes
6answers
5k views

Is adjusting p-values in a multiple regression for multiple comparisons a good idea?

Lets assume you are a social science researcher/econometrician trying to find relevant predictors of demand for a service. You have 2 outcome/dependent variables describing the demand (using the ...