Linked Questions

1 vote
1 answer
617 views

Does multivariate regression produce the same results as multiple, single regressions? [duplicate]

I've read a variety of answers on this topic and as far as I can see, the consensus is that multivariate regression is different from multiple, individual linear regressions. I also understand that in ...
user275010's user avatar
0 votes
0 answers
206 views

What does multivariate regression get us that several univariate regressions do not? [duplicate]

("Multivariate" regression in this post means a multidimensional response variable.) I have been playing with multivariate regression for the past two days, and I have noticed something that did not ...
Dave's user avatar
  • 67k
1 vote
0 answers
132 views

Why bother with multivariate regression? [duplicate]

There are a few books out there on how to do multivariate regression, but of course the literature isn't as massive and detailed as univariate regression models. So why bother with multivariate ...
Kahi's user avatar
  • 11
0 votes
0 answers
39 views

Does multivariate multiple regression take into account correlated outcomes? [duplicate]

Thank you so much for your time. I am running an analysis where I explore the association of the same predictors across multiple outcomes (these outcomes are correlated). My understanding is that when ...
Emma's user avatar
  • 1
186 votes
11 answers
236k views

When is it ok to remove the intercept in a linear regression model?

I am running linear regression models and wondering what the conditions are for removing the intercept term. In comparing results from two different regressions where one has the intercept and the ...
analyticsPierce's user avatar
97 votes
7 answers
192k views

Explain the difference between multiple regression and multivariate regression, with minimal use of symbols/math

Are multiple and multivariate regression really different? What is a variate anyways?
Neil McGuigan's user avatar
154 votes
3 answers
90k views

Removal of statistically significant intercept term increases $R^2$ in linear model

In a simple linear model with a single explanatory variable, $\alpha_i = \beta_0 + \beta_1 \delta_i + \epsilon_i$ I find that removing the intercept term improves the fit greatly (value of $R^2$ ...
Ernest A's user avatar
  • 2,392
82 votes
2 answers
79k 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 ...
Andrej's user avatar
  • 2,223
27 votes
8 answers
101k views

When forcing intercept of 0 in linear regression is acceptable/advisable [duplicate]

I have a regression model to estimate the completion time of a process, based on various factors. I have 200 trials of these processes, where the 9 factors being measured vary widely. When I perform a ...
Zack Newsham's user avatar
13 votes
1 answer
15k views

Why does statsmodels.api.OLS over-report the r-squared value?

I am using statsmodels.api.OLS to fit a linear regression model with 4 input-features. The shape of the data is: ...
dhrumeel's user avatar
  • 301
8 votes
2 answers
8k views

Simple, multiple, univariate, bivariate, multivariate - terminology

I do realise (some of) this has already been addressed here (e.g., Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?, Explain the difference between multiple ...
Tilen's user avatar
  • 840
8 votes
1 answer
7k views

How can MANOVA report a significant difference when none of the univariate ANOVAs reaches significance?

I would just like to ask if it is normal for the values from my multivariate tests to be significant but for the values from my univariate tests of between-subjects effects table to be insignificant. ...
kea's user avatar
  • 83
5 votes
2 answers
5k views

Why is it possible to have a non-significant MANOVA but multiple significant univariate ANOVAs?

The only source I have for this being possible is this wikiversity page on MANOVA, but it does not explain why it is possible.
user1205901 - Слава Україні's user avatar
12 votes
1 answer
5k views

Multivariate linear regression vs. several univariate regression models

In the univariate regression settings, we try to model $$y = X\beta +noise$$ where $y \in \mathbb{R}^n$ a vector of $n$ observations and $X \in \mathbb{R}^{n \times m}$ the design matrix with $m$ ...
Roy's user avatar
  • 849
2 votes
1 answer
2k views

Linear regression with vector outputs

Suppose I wanted to make a linear fit to a dataset with vector input and output, by minimizing the least square error. Then the square error equation would be $$E = \frac{1}{2}\sum_i(W\vec{x}^{(i)} - \...
Brain Stroke Patient's user avatar

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