Questions tagged [multivariate-regression]
Regression with more than one response (dependent) variable.
317
questions
2
votes
1answer
33 views
Binary logistic regression model shows unrealistic OR and 95% CI
I've just done a multivariate regression analysis, using a p-value from bivariate regression analyses of <0.20 as a cut-off to determine which variables will be included in the multivariate model.
...
0
votes
0answers
23 views
Media Mix Modelling approach?
I need some guidance on the media mix modeling approach as I am fairly new to it and have been researching about it only for the last few days. I have six months' data which contains daily level ...
1
vote
1answer
16 views
When should multivariate GLM(M)s be used?
Suppose I have a set of $k$ dependent variables which are all correlated with each other and known a priori that they are dependent. I also have a set of $p$ independent variables (predictors) which ...
0
votes
1answer
20 views
Signs of MarginalEffects and CoefficientEstimates in Multivariate Probit
Could someone explain that the sign of coefficient estimates and their corresponding marginal effects in the Multivariate Probit Model is the same or they could be different? IF they are different, ...
1
vote
0answers
30 views
Multiple post-hoc tests after Multivariate GLM/MANCOVA
I have three groups, where I am doing a multivariate GLM/MANCOVA to test for multivariate differences between groups (6 DVs), adjusting for 2 covariates. I would like to do post-hoc tests to see which ...
0
votes
0answers
12 views
Generalized Linear Model with vector response (multivariate target): what is the formal definition?
What is the formal definition of the Generalised Linear Model (GLM) with vector response (multivariate target)? Is there a text, which clearly shows how the linear regression model with a vector ...
0
votes
1answer
48 views
The correct tool for testing statistically likely source of endpoint?
Background
Whilst I have some experience in statistics, I am not trained in the field and so am at somewhat of a loss with respect to what tool I should employ in the following scenario.
I have a ...
1
vote
1answer
21 views
Joint (or multivariate) model to predict two correlated time-to-event outcomes
this is a general question.
Say you want to predict two time-to-event outcomes, the time until chronic heart disease, and time until diabetes. You think these outcomes are likely to be correlated, i.e....
0
votes
1answer
23 views
What test to run for multiple IVs predicting multiple DVs?
I am doing my dissertation on the relationship between schizotypy and cognitive functioning. For my main research question, I want to understand if certain subscales of the STA (schizotypy ...
0
votes
0answers
17 views
Estimates from MCMCglmm multivariate regression
I'm running a multivariate regression on two response variables (X and Y) using MCMCglmm in R. X is a continuous variable (family = Guassian) while Y is a binary response variable (family = threshold)....
0
votes
2answers
35 views
How can I fit a smoother to a 2-dimensional parametric curve (with R)? [closed]
I have a dataset of GPS traces of lat/lon and time for some routes (ex: NYC-Boston). Since I have multiple traces for each route, I would like to find the "average" trace, or some kind of ...
1
vote
1answer
31 views
Why reversing a continuous measure leads to a non-significant correlation coefficient
Background: I'm analyzing correlation between two behavioural types (boldness and aggression). Boldness values are continuous (range: 2 to 1195) and it's unit of measurement is in seconds (latencies). ...
0
votes
1answer
39 views
Linear hypothesis test for multivariate linear model (`mlm` object) in R
I'm running a mulivariate linear model like this one:
...
0
votes
0answers
9 views
Prediction based on multivariate explanation
I have a set of variables that when summed, make up an aggregate variable. When I regress the aggregate onto a non-specified timeseries, I get an insignificant result. The same happens when I regress ...
1
vote
0answers
86 views
MANOVA test statistics with GLM Multivariate Multiple Regression in R
Good afternoon! I am currently working on my master thesis and I am a bit stumped on how to proceed practically with my analysis.
I am running a Multivariate Multiple analysis on a dataset, so I have ...
0
votes
0answers
11 views
Multivariate regression standard error
This is an easy question I think, but I am asked to calculate the confidence interval for the difference in two females' earnings. I have calculated their earnings based on the dummy variables and ...
0
votes
0answers
28 views
What is an appropriate model for equation of state?
What I want
A function with pressure and temperature as input parameter and enthalpy as output. I am using R but any hint for choosing an algorithm/model would be ...
0
votes
1answer
18 views
Interpreting interaction effects in regression
Suppose we are regressing Y = aX + bD + cXD. a and b are main effects of variables X and D, and c is the interaction effect. Assume both X and D are continuous variables.
How to interpret the effect ...
0
votes
0answers
13 views
Model selection and interaction terms in multivariate regression analysis of compositional data (Dirichlet regression)
I am currently exploring Dirichlet regression models to model fatty acid compositional data. I am using 2 categorical predictors and 1 continuous predictor (treatment group, sex, and total lipids).
...
0
votes
0answers
56 views
MSPE predictor of MA model
Assume $e_i=(\epsilon_i+\epsilon_{i+1})/2, i=1,...,n$ where $\epsilon_1,...,\epsilon_{n+1}$ are iid with mean zero and variance $\sigma^2$. Then $e_i$ are the moving average errors. Now, consider the ...
0
votes
0answers
23 views
Interpretation of the coefficients from quantile regression with dummy independent variables only
I have a data set with only categorical variables, some are nominal and some are ordinal, but I assume there will be non-linear relationship between output and order of ordinal variables, so I have ...
1
vote
0answers
24 views
Bayesian multivariate regression
I am trying to solve the below multivariate regression problem by building a fully Bayesian model-
\begin{align*}
\mathbf{Y} = \mathbf{X}\mathbf{B} + \mathbf{E}
\end{align*}
where $\mathbf{Y} \in R^{n\...
0
votes
0answers
20 views
Multiple dependent variable model, What model to use?
I need to develop a model to predict the best budget allocation scheme for x budget between n posibilities (products or product types) for a certain person. Aside from the budget, there are multiple ...
2
votes
1answer
21 views
How does AMOS or other SEM/path analysis software estimate missing data?
I'm currently writing a paper as a hopeful publication. I'm using AMOS to run path models. But I think my question can apply when utilizing other path analytical software.
I have one path model that ...
0
votes
0answers
11 views
Optimizing Frobenius norm in R
Suppose that $Y \in \mathbb{R}^{n \times p}$, $X \in \mathbb{R}^{n \times d}$. Is there a function in R that gives the optimal solution $\hat{B} \in \mathbb{R}^{d \times p}$, which minimizes $\Vert Y-...
0
votes
0answers
27 views
How to perform multivariate multiple regression using quantitative variables in R
I would like to try multivariate multiple regression with 5 dependent variables, 3-4 independent variables. All are continuous quantitative variables and are standardized data (because some of them ...
1
vote
1answer
19 views
Scaling explanatory variable by constant in multivariate linear regression
Suppose I have a model with $n$ observations $$Y_i = \beta_0 + \beta_1 x_{1i} + \beta_2 x_{2i} + \varepsilon_i$$ and suppose that I obtained estimates $\hat Y$, $\hat \beta_1$, and $\hat \beta_2$ from ...
2
votes
2answers
38 views
consistent estimation of quantiles (without overlapping quantiles)
I would like to forecast quantile ranges. The observations are assumed to be heteroscedastic. Mostly, I am confronted with the problem that quantile regression results for different quantiles do ...
0
votes
0answers
13 views
MANOVA or difference scores?
I have a research design where participants are asked how much they want to donate to two different children in need. The goal is to measure whether they will be equitable (give equally to both ...
0
votes
1answer
25 views
Forecasting the daily visits when I have the data for other stores
I have the number of people visiting stores for each day, but sometimes one or several store do not send data for a particular day. How can I leverage the data I have for the stores that sent me data ...
0
votes
1answer
36 views
How to deal with different lengths of dependent variables for Multiple Multivariate regression?
So this question is probably part statistics and part r studio related. I want to run a Multiple Multivariate Regression with 13 dependent variables and 4 predictors. The 13 variables are scales from ...
0
votes
0answers
27 views
Proving residual/$\sigma \sim$ $N(0,1)$
I would like to proof that
$$\frac{Y_i - \hat Y_i}{\sigma} \sim N(0,1)$$
holds where I refere to the general multivariate regression case, i.e. $Y_i = x_i \beta + \epsilon_i$ with $\epsilon_i \sim N(0,...
0
votes
0answers
27 views
Why would a multivariate regression of two correlated output variables be worse than assuming independence?
I have 7 features and 2 outputs. The outputs are definitely highly correlated (wingspan and standing reach, which are two common measurements for basketball players). I have created two models using ...
1
vote
1answer
47 views
How to identify latent factors on only one observed variable
Is there an approach to identify latent factors impacting the outcome of only one observed variable?
I have a number of observations for one variable and assume that it is affected by two latent ...
0
votes
0answers
6 views
How to assign relation between categorical input and any given variables for Multivariate regression models with a backwards method in R?
I am kind of beginner level in R and I do apologize for any misunderstanding and typo-error. I am trying to perform a statistical analysis for a measurement, which is a function of time. I was told by ...
1
vote
0answers
34 views
Intuition for Hotelling's T^2 Test
I have been learning about Hotelling's $T^2$ test from Multivariate Statistics: Old School. The test is given by $T^2 = \nu\cdot\text{trace}(\bf{W}^{-1}\bf{B})$. The author shows that in the case of ...
0
votes
0answers
20 views
When building a linear regression model using PC1 from a PCA, does it matter that some of the variables explaining PC1 are collinear?
Let's say for instance, I measured a biological variable at different sites. I also measure a bunch of environmental variables, and I create a principal component analysis using those environmental ...
0
votes
0answers
28 views
Fitting a multivariate linear regression with different residual variance for each outcome (using a mixed effects model in R)
In a small simulation, I am fitting a multivariate normal model to predict two outcomes Y1 and Y2, while also modelling the covariance between them. This can be done through a mixed effects model (...
0
votes
0answers
146 views
Multivariate quantile regression group lasso in R
I'm trying to fit a multivariate sparse quantile regression model with group lasso. The regression is multivariate as there are several dependent variables, $Y=(y_1,\dots,y_k)$. The selected $X$s must ...
0
votes
0answers
14 views
Multivariate Regression with Unknown Number of Responses
I would like to perform a regression task in which the number of response variables differ for each observation. As a simple example, this could be taking a greyscale picture and aiming to determine a ...
4
votes
1answer
93 views
Testing equality of quantile regression slopes at different quantiles
How do I test if the quantile regression slopes are equal for different quantiles?
E.g. I run a quantile regression at 5% quantile, 50% quantile (median) and 95% quantile and obtain the slope ...
0
votes
0answers
33 views
Multivariate Multiple Regressions
I have 24 multiple regression equations (24 dependent series and 24 independent series) and want the coefficients to be equal.
How do I combine them?
I allow for correlation of errors and tried SUR, ...
0
votes
0answers
22 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 ...
1
vote
0answers
35 views
Investigate correlations in dependent variables: interpreting EFA
Background
I have a dataset that includes 5 dependent variables (different genes expression levels, all continuous) and independent variables (a categorical variable -treatment-, a few covariates and ...
0
votes
0answers
14 views
Is multivariate linear regression appropriate with a fully repeated measures design
I am trying to set up a multivariate linear regression model but am having difficulty figuring out as to whether it is appropriate for my dataset.
For a group of participants, I have 3 response ...
1
vote
0answers
426 views
Autoencoders For Multivariate Time-series Anomaly Detection
I have a multivariate time series of size (1e6, 15) and would like to fit a LSTM autoencoder. I prepare data with multivariate rolling windows (one step rolling) where each sample has (1, 5, 15) ...
0
votes
1answer
39 views
Multivariate Regression Tree
I need to build a Multivariate Regression Tree.
Looking at Scikit-learn's Multi-output Decision Tree Regressor it seems that what they do is define as many regressor as there are dependant variables. ...
0
votes
0answers
33 views
R-squared fot multivariate regression
I have an output of recalibrated VARX model, which means for each 500 points of my data set I have trained a model and predicted the next month values using that ...
1
vote
0answers
53 views
D-optimal design with nuisance parameters
I am a mechanical engineer trying to develope an optimal design of experiments in a problem with nuisance parameters. I would like to calculate the parameters $\mathbf{d}$ to optimally estimate ...
0
votes
0answers
263 views
Hyperparameter Tuning with Keras / Tensorflow for multivariate time series regression
The model
I am training a dense feed-forward NN using the Keras API on Tensorflow.
Each sample of the training set defines $\mathbf{X_t}$ and $\mathbf{Y_t}$ of an observed time period $t\in T$. Input ...
