Questions tagged [multivariate-regression]

Regression with more than one response (dependent) variable.

Filter by
Sorted by
Tagged with
0 votes
0 answers
24 views

Understanding types of LSTM and their use cases

I'm currently considering to use RNN/LSTM for a predictive modelling project that involves time-variant points. From looking at the following types of LSTM/RNN (in the picture below), I want to try ...
user avatar
0 votes
0 answers
16 views

Adjusted $R^2$ (R-squared) for multivariate regression

For univariate or single independent variable regressions, this formula can be used (details here): $$R^2_{adjusted} = 1- \dfrac{SSRes}{SSTotal}\dfrac{n-1}{n-p}$$ However, I cannot find a similar ...
user avatar
0 votes
0 answers
8 views

Multivariate multilevel ordinal regression

I am looking to estimate a multivariate multilevel ordinal regression model (preferably via the ordered logit) in $R$ using non-bayesian methods. Is anyone aware of a package that does this? If not, I ...
user avatar
0 votes
0 answers
29 views

Working with a Dataset containing multivatiate numerical Timeseries which is highly sparse

I am working currently on a private dataset that has a similar structure to MIMIC-III. The dataset has following structure: p Patients, e Examinations, t Timepoints For every patient there are ...
user avatar
  • 1
0 votes
0 answers
41 views

Regression with multiple dependent variables

I am looking to derive the regression equation for the data in the table below however i am faced with two problems, using Excel, regression equation can't be derived due to the NAs in the data multi-...
user avatar
1 vote
1 answer
26 views

I have set of features to relate to two different values. When I made a regressor for only one it worked well but if i use two it does not?

I have a set of 33x1 features (x) and they can be related to different two values in (y) and I have 1203985 observations. Using np.shape() you can see the dimensions of x and y. x= (1203985, 33) y=(...
user avatar
0 votes
0 answers
11 views

DF of multivariate multilevel random effects model

my question is concerning a multivariate multilevel random effects design. I have one between-subjects variable, gender. My outcome variable is composed of several (...
user avatar
0 votes
0 answers
17 views

Likelihood for left-censored data in one dimension and uncensored in another dimension

I need to maximize a likelihood for parameters $\vec{\theta}$ given a model $\vec{g}(x_i,\vec{\theta})$ (let's say this is a non-linear black box) and observed data $(x_i,\vec{y}_i)$. The dependent ...
user avatar
  • 1
2 votes
2 answers
196 views

Visualizing multivariate multiple regression of continuous data in R

I have created a multivariate multiple regression model with 3 dependent and 3 independent variables in R, and would like to generate meaningful visualizations. All variables are continuous. When ...
user avatar
0 votes
0 answers
17 views

Multivariate Multiple Regression table template

I need a table template for Multivariate Multiple Regression Analysis (2 IVs and 2 DVs). If anyone has, please share. Actually, I am conducting step_wise multiple regression analysis for predicting 2 ...
user avatar
0 votes
0 answers
22 views

How to Treat Multivariate Gaussian Processes

I am trying to predict time-series (and forecast) with Gaussian Processes(GPs). To perform this task, I decided to apply GPs in a multivariate regression fashion. Most of the GP examples I have seen ...
user avatar
  • 1
0 votes
0 answers
9 views

Missing values of two variables collide

I am performing multivariate regression in MPlus with survey data. The issue is that two predictors (from two different data collection years) do not have any common data: people who answered on ...
user avatar
  • 1
1 vote
1 answer
27 views

Multivariate Regression with Two Different Types of Response

Problem Setting: I have an interesting question related with longitudinal study and multivariate regression. I found that in lots of biomedical studies, multiple discrete and continuous endpoints are ...
user avatar
  • 21
0 votes
1 answer
25 views

How analyze annual data with one IV and multiple DVs

I'm currently working with a data set that includes multiple variables associated with each of 10 years of data. The basic structure, with (example hypothetical) variables in caps, is from YEAR to ...
user avatar
  • 31
0 votes
0 answers
42 views

How to validate and train a multivariate multiple regression model with multiple responses with R?

I would like to validate the accuracy of my model and train it. For this MMR I have used four dependent variables (y1, y2, y3, y4) and two independent variables (x1 and x2) Firstly, I worked with R ...
user avatar
  • 1
0 votes
0 answers
50 views

Seasonality in Independent Variables

There are many questions on why we need to remove seasonality. E.g. this and this. My question is slightly different. Do, we need to remove seasonality from independent variables as well when doing ...
user avatar
  • 5,844
1 vote
1 answer
103 views

Multivariate regression - test difference between coefficients

I am trying to figure out how to test the difference in slopes for the same explanatory variable in a multivariate linear regression. What type of test should be used and how can I perform this using ...
user avatar
  • 69
0 votes
1 answer
43 views

What does an interaction with a confounder mean within a multivariate regression analysis?

In a multivariate regression analysis, I examine the effect that a treatment method has on subjects' hemoglobin levels. Since this is a retrospective study, I could not control for gender (or age) by ...
user avatar
  • 25
0 votes
0 answers
34 views

Auto. Arima and ARIMAX for multi variate time series forecasting

I'm trying to do multivariate time series forecasting using the forecast package in R. The data set contains one dependent and independent variable. From the cross-correlation the 0 day lag of the ...
user avatar
2 votes
1 answer
574 views

ARIMAX and auto.arima for multivariate time series forecasting in R

I'm trying to do multivariate time series forecasting using the forecast package in R. The data set contains one dependent and independent variable. From the cross-...
user avatar
0 votes
1 answer
129 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)} - \...
user avatar
0 votes
0 answers
18 views

Determine if two groups differ for a series of binary variables - logistic regression

I am trying to determine how to analyze my dataset. I have two stimulus categories (Type 1 and Type 2) and then a series of variable observations that are binary (did respond/didn't respond, did ...
user avatar
0 votes
0 answers
45 views

How is this equation deduced?

These two equations are from the book Gaussian Process for Machine Learning. First we already have equation (2.8). $p(\mathbf{w}|X, \mathbf{y}) ∼ N (\frac1{\sigma_n^2}A^{−1}X\mathbf{y}, A^{−1})$ (2.8) ...
user avatar
0 votes
1 answer
39 views

How to choose the right variables for the logistic regression in an observational study?

I have read answers to the similar questions here and read other resources but I could not find a solid answer to this point. Sorry for my simple terminology. While analyzing the data from an ...
user avatar
2 votes
1 answer
51 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. ...
user avatar
0 votes
0 answers
96 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 ...
user avatar
1 vote
1 answer
43 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 ...
user avatar
0 votes
1 answer
72 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, ...
user avatar
1 vote
0 answers
117 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 ...
user avatar
  • 23
0 votes
0 answers
20 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 ...
user avatar
0 votes
1 answer
50 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 ...
user avatar
  • 25
1 vote
1 answer
35 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....
user avatar
  • 315
0 votes
1 answer
33 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 ...
user avatar
  • 1
0 votes
0 answers
38 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)....
user avatar
  • 21
0 votes
2 answers
43 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 ...
user avatar
  • 141
1 vote
1 answer
42 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). ...
user avatar
  • 21
0 votes
1 answer
58 views

Linear hypothesis test for multivariate linear model (`mlm` object) in R

I'm running a mulivariate linear model like this one: ...
user avatar
0 votes
0 answers
13 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 ...
user avatar
  • 1
1 vote
0 answers
319 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 ...
user avatar
  • 11
0 votes
1 answer
27 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 ...
user avatar
1 vote
0 answers
56 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\...
user avatar
  • 185
2 votes
1 answer
53 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 ...
user avatar
  • 49
0 votes
0 answers
19 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-...
user avatar
  • 111
1 vote
1 answer
22 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 ...
user avatar
2 votes
2 answers
58 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 ...
user avatar
  • 21
0 votes
1 answer
27 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 ...
user avatar
0 votes
1 answer
250 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 ...
user avatar
0 votes
0 answers
28 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,...
user avatar
1 vote
1 answer
56 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 ...
user avatar
1 vote
0 answers
43 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 ...
user avatar

1
2 3 4 5
7