Questions tagged [multivariate-regression]
Regression with more than one response (dependent) variable.
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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 ...
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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 ...
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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 ...
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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 ...
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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-...
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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=(...
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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 (...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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-...
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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)} - \...
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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 ...
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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)
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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 ...
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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.
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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 ...
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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 ...
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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, ...
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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 ...
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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 ...
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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 ...
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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....
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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 ...
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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)....
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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 ...
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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). ...
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Linear hypothesis test for multivariate linear model (`mlm` object) in R
I'm running a mulivariate linear model like this one:
...
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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 ...
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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 ...
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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 ...
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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\...
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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 ...
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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-...
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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$$ and suppose that I obtained estimates $\hat Y$, $\hat \beta_1$, and $\hat \beta_2$ from ...
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consistent estimation of quantiles (without overlapping quantiles)
I would like to forecast quantile ranges. The observations are assumed to be heteroscedastic. Mostly, I am confronted with the problem that quantile regression results for different quantiles do ...
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Forecasting the daily visits when I have the data for other stores
I have the number of people visiting stores for each day, but sometimes one or several store do not send data for a particular day. How can I leverage the data I have for the stores that sent me data ...
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How to deal with different lengths of dependent variables for Multiple Multivariate regression?
So this question is probably part statistics and part r studio related. I want to run a Multiple Multivariate Regression with 13 dependent variables and 4 predictors. The 13 variables are scales from ...
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Proving residual/$\sigma \sim$ $N(0,1)$
I would like to proof that
$$\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,...
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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 ...
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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 ...
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