Questions tagged [multivariate-regression]
Regression with more than one response (dependent) variable.
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What is the distinction between multivariate normality of the outcome and of specific parameters?
Is assuming multivariate normality of the errors of multiple regression equations equivalent to assuming multivariate normality of e.g. just the regression coefficients, just the intercepts, and/or ...
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SELECTION OF MULTIVARIATE TECHNIQUE
Can someone please explain what does single relationship mean in the below image for the selection of multivariate regression techniques? In "Several dependent variables in a single relationship&...
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Multivariate regression with dependent variables on an interval
I want to do a regression what the probability is of event being True (=P(E)). This dependends on three variables, let's say A, B and C.
SO: P(E) = X1 * A + X2 * B + X3 * C
My data consists of the ...
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Can I use the multivariate response predictions of some variables as covariates to predict another correlated response?
I have covariates to predict 3 multivariate response variables, and would like to use those 3 predictions to predict another forth variable that is also correlated with the other variables:
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Can I combine dichotomous and continuous outcomes into a single regression model?
I am doing analysis on an educational product that aims to predict what impacts whether or not a student gets a question correct or incorrect. The DV includes item scores from four different question ...
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Multivariate forecast vs. forecast with exogeneous factors
If I wanted to forecast sales in a grocery store and I knew factors that would influence grocery sales, would there be a reason why I should use a multivariate time series model vs. time series models ...
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How do I model relative time spend doing different behaviours?
I have a dataset comprising observations of ducks performing different behaviours. Specifically, ducks were observed for 1 minute each, and during each 1 minute observation the amount of time that ...
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Multivariable Cox Regression Analysis
I would like to know if in multivariable Cox regression analysis there is a way to yield only models that include a variable of interest (and if no model is statistically significant to just answer ...
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Multivariate regression and process control
I have a question regarding process control with the use of multivariate regression.
The setup is as follows: say we have some data, representing the results of a plant process. Specifically, several ...
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What approach would you recommend to find the dependent variables that are most affected by the predictors in a multivariate analysis?
I used to handle most of the time species count data. The approach in my group was to do a multivariate analysis of variance, and if there were many dependent variables, we tried to find the ones ...
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interaction term in Cox PH model
I have a question with regard to interaction term in Cox PH model.
I'd like to analyze the impact of variable A on cardiovascular (CV) event.
Variable A levels are different according to sex, although ...
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VAR models for multiple and multivariate time series prediction
I wanted to know how viable is to use VAR models for modelling multiple multivariate time series?
A little bit of context to the problem: I want to predict demand for a given car, based on the car ...
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How to calculate a cross-product like R^2?
$\lbrace Y_1, Y_2, \boldsymbol{X} \rbrace$ are jointly normally distributed (it is not essential to assume normality, I think). Let $\Sigma_{X}$ be the variance-covariance matrix of $\boldsymbol{X}.$ ...
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How to construct a confidence interval for the coefficients of a multivariate regression with dependence between dependent variables?
Suppose we have two linear regression models $y_1=a+bx+\epsilon_1$ where $\mathbb[\epsilon_1]=\sigma_1$ and $y_2=c+dx+\epsilon_2$ where $\mathbb[\epsilon_2]=\sigma_2$. In other words, I am using the ...
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Extracting factors of a large (dimension m,n) matrix M which correlate with a vector P (length m)
So I'm dealing with a large gene expression dataset (m sample by n genes, where m ~ 1000 and n ~ 20,000). For each of these samples, a phenotype of interest P exists. I'd like to be able to say ...
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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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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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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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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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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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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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