Questions tagged [multivariate-analysis]
Analyses where there is more than one response or dependent variable of interest. This can be contrasted with "multiple" or "multivariable" analysis, which typically implies more than one predictor or independent variable.
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R - multivariate random forest for variable importance
A little background - I'm trying to use multivariate random forest modeling to understand the importance of environmental variables on microbial communities (illumina sequencing) along a latitudinal ...
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1answer
18 views
Difference between using a propensity score for matching vs. regression analysis
So I am confused on what the difference is if I match patients based on propensity scores vs. using the propensity score and then applying that into a multivariate regression analysis? Is there a ...
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4 views
Equivalent of majority class baseline in multi label models
Suppose I have a classifier output as follows;
X | Y | Z | H
0 | 1 | 0 | 1
0 | 0 | 0 | 0
Where we have four classes, each class is a binary encoded vector. The ...
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1answer
9 views
Does adding more than 1 dependent variable to SEM have purpose other than to control for correlation between dependent variables?
I am pretty new to SEM, so when I first saw a SEM model with 2 DVs, I wanted to know the difference between having 2 DVs and running SEM process twice for each DV.
From what I understand, having more ...
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35 views
Using Hotelling's T-statistic to find an elliptic confidence set
The problem: We have samples of sizes ${n_1} = 25,{n_2} = 15,{n_3} = 30$ drawn independently from $N\left( {{\mu _i},{\sigma ^2}} \right),i = 1,2,3$ (normal distributions with same variance). We have $...
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9 views
What are common measures of error for cross validation of a multivariate outcome?
I have a multivariate outcome $Y_i\in\Re^m$ for $i\in\{1,2,...,n\}$ that I would like to build a predictive model for. Denote predictions of $Y_i$ to be $\hat{Y}_i$ (predicted from a model estimated ...
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33 views
Estimating a VAR model via OLS
I am looking at Vilasuso (2001), who says that when using least-squares to estimate causality in mean, there is significant size distortion if the conditional variances are correlated.
My question ...
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6 views
Providing Statistical evidence that credit portfolios have different risk behaviour
I work in the risk department of a credit company and I was asked to analyse and bring some statistical evidence that two portfolios have different risk behaviour. So, my goal is to find if, for ...
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2answers
62 views
Predict a vector of values with constraints? [duplicate]
I am aware of a variety of methods for simultaneously predicting multiple outcomes known sometimes as multivariate regression/analysis. However, my situation is a little more special. I am trying to ...
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6 views
Kalman/HMM for (short) multivariate time series from a sample with missing values
The problem in short:
I want to estimate (?) a lag-1 Markovian hidden process for offline multi-variate discrete-time time series with continuous distributions via smoothing, with no dimensionality ...
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5 views
Orthogonalised Impulse Response Functions in Stata
This might be a really basic question for some of you but I have been looking up how to interpret impulse responses but most of the answers that were presented did not quantify the responses but ...
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7 views
Forecasting a DCCGARCH model estimated by the ccgarch package
How can one predict a dcc-garch model in R using parameters estimated from dcc.estimation from the package ccgarch?
MWExample:
...
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17 views
What is the correct way to follow up a multivariate multiple regression?
I recently conducted a study in which I used a series of multiple linear regressions to predict different outcomes (y1-y6) using the same set of predictor variables (x1-x8). My hypotheses were that ...
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7 views
When do we use a multi-variate analysis instead of ANOVA and vice-versa? Noob apologies [closed]
Context: I am an intern in a manufacturing plant currently(after studying mechanical engineering). The general dealings with data are about quality control and problem solving.
I was making my way up ...
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7 views
Term for modeling multivariate distribution by modeling iterative conditionals
Suppose I have a multivariate random variable $Y_1,...,Y_k$ for which I would like to model the joint distribution. To be clear, there is not a natural ordering to $Y_1, ..., Y_k$, e.g., they are not ...
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1answer
20 views
Conserve correlation with simulate data
let me explain you the process, I have random variables in a matrix $X_1$: $260\times3$.
I have my correlation matrix $\rho_1$: $3\times3$ from my matrix $X_1$.
Now I use a Cholesky decomposition ...
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21 views
How to proceed when testin for non-linear relationships between variables
I'm trying to predict the amount of money a customer spends on a product by using linear regression.
I had the hypothesis that there was a non-linear connection between the Product_Category, the ...
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1answer
25 views
Imputing missing values from multivariate Normal Distribution
Let's say my data of dimension $3$ has a multivariate normal distribution with known mean vector $\mu$ and covariance matrix $\Sigma$
I then observe a sample from the distribution but with $1$ value ...
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24 views
Is MLE or some other estimation procedure possible for multivariate bernoulli? [closed]
Let $\bf{x_1}$, $\bf{x_2}$ … $\bf{x_n}$ ~ independent k-variate Bernoulli random vectors, such that $x_{i1}$ ~ $Ber(p_1)$, $x_{i2}$ ~ $Bern (p_2)$ etc. The elements of each vector are not independent ...
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18 views
Change of variables: 4-dimensional PDF to 2-dimensional PDF
I have a 4-dimensional joint-PDF between variables $X_1,X_2,X_3,X_4$ which are all Gaussian. I want to transform this into a 2-dimensional joint-PDF between new variables $Y_1=Y_1(X_1,X_2,X_3,X_4)$ ...
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11 views
Remove insignificant or multicollinearity variables?
If bivariate correlation has some variables that are insignificant and some with multicollinearity, which do you remove first before re-running (in order to run linear regression afterwards)?
I used >...
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8 views
Sign test for multivariate time series models
I'm trying to model 98 covariate time series (using CARBayesST in R). I want to make sure that the residuals look nice, so a sign change test is of interest (since I saw that some series had a ...
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23 views
Computing the credible region from a pre-computed list of function evaluations
I have a nonlinear function of four variables $f(x_1,x_2,x_3,x_4)$. This function outputs three things: $[y_1, y_2, y_3]$.
(In reality, the function $f$ is a simulation which solves the equations of ...
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50 views
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1answer
20 views
Multivariate (Multi-responce) for negative binomial (GLM) in R
I developed a multivariate linear regression using lm() function in R. However, I am having trouble coding a Multivariate model in R for glm(), especially for the negative binomial.
Can anyone point ...
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242 views
Validity of confidence interval for $\rho$ when $X\sim N_3(0,\Sigma)$ with $\Sigma_{ij}=(\rho^{|i-j|})$
Suppose $X\sim N_3(0,\Sigma)$, where $\Sigma=\begin{pmatrix}1&\rho&\rho^2\\\rho&1&\rho\\\rho^2&\rho&1\end{pmatrix}$.
On the basis of one observation $x=(x_1,x_2,x_3)'$, I ...
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1answer
37 views
Hypothesis testing: significance
i conducted a survey that aims to find out if Australians prefer Australian phones over Chinese phones.
My hypothesis states: Australians prefer Australian phones over Chinese phones
This was ...
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0answers
18 views
Incorporating multiple categories to understand relationships between them in a sequential model
I have successfully built a a sequential model to stratify different organs of some genomic data that I have, and this works really well and with a high accuracy too. However, this is also time series ...
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7 views
Measuring how much variance in a multidimensional sequence is explained by a sequence of scalar measurements on the samples
Suppose I have a set of $m$ samples, each of dimension $d>1$, organized into a matrix $X_{d\times m}$. I also have vectors $y_{i}$ of length $m$, in which each entry is some measurement on the ...
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1answer
25 views
Factor importance in multivariate experiment
I'm trying to analyze a multivariate experiment and show impact of each factor in a multivariate experiment. The general way to do this analysis would be to perform ANOVA:
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1answer
12 views
Test that predicts group membership from multi-variate data?
Context: Zoology undergrad dissertation. The format of my results will be % time individual birds spent doing certain activities (and possibly number of times an activity such as pecking was performed)...
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9 views
ANCOVA with two covariates
I was wondering if anyone know how to test the assumption of regression slopes for an ANCOVA with 2 covariates. Do I need to have separate interaction between the "groups" and age and then "groups" ...
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11 views
Handling data where the sample axis contains an elution profile
I have a 3-way data cube, where each sample is a 2D matrix. The sample axis contains samples every n-seconds (n = 7 seconds) but there is an ELUTION PROFILE, where the each sample appears and ...
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10 views
Should I use a MANOVA and then a two-way MANOVA or just the two-way MANOVA?
My research questions:
Is there an effect of the independent variable on the two dependent variables?
Is this effect of the independent variable on the two dependent variables stronger for females ...
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1answer
13 views
two-way MANCOVA
I am currently trying to run a two way MANCOVA as I have to independent variables with 2 levels each 1)sleep chronotype (late and early) and weekly sleep loss (high and low) . I have four dependent ...
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12 views
How can I classify a person's score according to my discriminant variable, in a discriminant function? (multiple discriminant analysis) [closed]
I'm doing a research on 5 types of entrepreneurship (dependent variable) and personality traits (5 independent variables). As you can tell, I did a discriminant analysis as a "plus" for my prior ...
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1answer
45 views
SVD matrixes do not coincide with Eigen decomposition for covariance matrix [duplicate]
I am comparing the output from the singular value decomposition with the eigendecomposition of the covariance matrix (symmetric matrix). I am expecting that the Eigenvector and a non-diagonal matrix ...
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1answer
11 views
discover a latent (confounding) effect in a model
Lets say I want to model the relationship between sales and 3 predictors: marketing, competition and visits (mkt, ...
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2answers
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categorizing a variable turns it from insignificant to significant
I have a numeric variable which turns out not significant in a multivariate logistic regression model.
However, when I categorize it into groups, suddenly it becomes significant.
This is very counter-...
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1answer
24 views
Which statistical analysis to use on ordinal questionnaire data?
I would like to analyze data on questionnaire scores on quality of life between two different groups. There are 20 quality of life questions, all with responses on a Likert scale 1-7. So I have an ...
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42 views
Time series with python
I've a dataset in following format
day,8am,9am,10am,......,8pm
2012-1-1,0.3,0.2,0.21,.....,0.4
2012-1-2,0.32,0.19,0.22,.....,0.45
................
I'm not sure ...
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20 views
Bootstrapping non-random samples
I perform some analysis (with the goal to select some relevant variables that are related between two experiments) on a group of samples (n = 158) but I would like to know how robust are, before going ...
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1answer
34 views
Multi-year and multi-location correlation or regression?
I have fire activity data (i.e. number of fires) and a series of factors (e.g. precipitation, tree cover loss, distance to nearest forest, etc...) that can potentially explain it. I have all this data ...
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24 views
Incorporating linear combination predictions into multiple regression
Let's say I have a predictor $p_1$ of the form: $\textbf{y} = f(\textbf{x})$
Let's suppose that I found another predictor $p_2$ of the form: $E[y_1 - y_0] = c$ (e.g. I have a predictor of linear ...
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1answer
17 views
Which command should be used in SPSS for calculating p value without confounding factors effect?
In a study, we have the disease as dependent variable ( 0 or 1 patient or healthy); some independent variables are real and some of them are confounding (some of varibles are quantitative and some of ...
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39 views
Showing that $(l'\Sigma l)\chi_p^2 = (l'S l)\frac{(n-1)p}{n-p} F_{p,n-p}$
Let $X_1,\cdots X_n$ be i.i.d. $N_p(\mu,\Sigma)$. I have that when $\mu$ and $\Sigma$ are unknown that the Scheffe type method gives $(1-\alpha)100$% confidence intervals for all linear combinations $...
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1answer
12 views
What are criteria to select the variables to include in a multiple Cox regression model
I have a group over about 500 subjects and want to perform a cox-regression to find predictors of an event taking into account the time to event. I have 12 potential predicting variables that I want ...
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1answer
69 views
Expectation and Variance of dot product of a random vector and random linear combinations of vectors from the same distribution?
Let's say we have a multivariate distribution $D$ which generates random $n$-dimensional vectors $x$ for us ($x \in R^n$). We know that the dimensions of vector $x$ are correlated, and that each ...
2
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1answer
35 views
How to show sample correlation is sample covariance for standardized values?
Given a matrix $X$ and the resulting sample correlation matrix $R$, consider the standardized observations:
$$\frac{(x_{jk} - \bar x)} {\sqrt{S_{kk}}} \quad k=1,2,...,p \quad j=1,2,...,n$$
Show that ...
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0answers
24 views
Permutation tests for paired data with several variables
I am trying to answer my own previous question, with a permutation method.
I have a reference method $M_{ref}$ that I would like to compare with other methods $M_1$, $M_2$, $M_3$ when taking ...
