This tag is a signal that the question focuses on a problem particular to multivariate analysis, such as multiple correlations or interactions.

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0
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1answer
13 views

How to blend multiple time series models?

I have three different linear, multi-variate time series models with a best fit against the same observed value $Y$ at 1 minute, 3 minutes and 10 minutes horizons respectively. Each model is using ...
0
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1answer
66 views

How can a regression be significant yet both predictors be non-significant? [duplicate]

I know this question has been asked in a slightly different form here. But my question differs and because of the forum rules I can't post on that thread. I have 2 independent variables, n=32, highly ...
0
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1answer
31 views

How to run main effects and interactions in a stepwise regression?

I am using multiple regression with the backward elimination method. I have one control variable (social desirable responding) and four predictor variables (gender and three self-esteem constructs). ...
-3
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0answers
16 views

One independent variable and many dependent variables [on hold]

My independent variable is (CEFFAS) Community Education for Family Formation via Alternating System. My dependent variables are Entrepreneurial Capacity such as Risk Taker; Competitive; Innovative; ...
0
votes
0answers
18 views

How to interpret Dickey Fuller (DF) test results in R (for unit test)

I read 1) Intuitive explanation of unit root and 2) http://www.r-bloggers.com/unit-root-tests/ for doing unit root test. I have basic questions: 1)should I check for unit root on both 'x' and 'y' ...
0
votes
1answer
41 views

problems to build the linear multiple regression in R and to explain the output [on hold]

I have a problem to build and to explain the linear multiple regression. I have a data set called Cars93 with 26 variables (numeric and not numeric) and 93 ...
4
votes
1answer
89 views

Regression where the dependent variable is the difference between two correlated variables — bias and other issues to consider

I am interested in estimating a regression that looks like this: $(x_{1,i} - y_{i} )_{i} = x’_{i}*\beta + \epsilon_{i}$ (1) However, I am not sure if doing this—in this form—is appropriate. ...
0
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0answers
20 views

Is there a way to model the error term in a linear regression with R?

I'm tryin to estimate a pretty basic regression. I have a dataset containing x and y and would like to esimate the following ...
0
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0answers
27 views

piloting a multinomial logistic regression model

I have 11 variables in my data set. farmers Group(1,2,3,4 this is my dependent variable) Independent variables Total holding ,Crop area , barn capacity.....and barn capacity extent match and YPH. ...
-1
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0answers
24 views

How can I interpret a multiple regression with categorical and ordinal variable? [on hold]

Help me please ! How can I interpret a multiple regression with categorical variables (by using dummy variable)? The question is that I want to find statistical significance between features and ...
1
vote
1answer
37 views

Can I compare two regression coefficients

I am comparing treatment outcome to two therapeutic treatments. Specifically, I am looking at how attachment moderates the relationship between therapeutic alliance and outcome. I hypothesize that the ...
-2
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0answers
14 views

polynomial regression model

Please, could you help me in answer on my question which it is as follows: I have 7 factors with 3 levels and no. of experiments are 27 tests, Can I build polynomial regression model with these data ...
0
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0answers
8 views

Count variable as control variable in regression in SPSS

I'm doing a research on development of audit fees in 2005-2012. I'd like to see if there's a downward or upward trend in them. I have made a count variable of the years (2005=1 2012=8) and now should ...
1
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0answers
24 views

How to do multiple regression with within-subject independent variables using SPSS?

I have two groups of subjects, both undergoing two experimental conditions. During the experimental conditions, the subjects take questionnaires for evaluation of the mood states, and blood pressure ...
0
votes
1answer
25 views

Multlinear regression: analysis of residual of transformed response and predictor variables

In the first step of modeling a regression equation I came up with the following model: $T_c = 26.73 + 0.042{\rm Sc} + 0.247{\rm Lc} - 14.709{\rm Lf} + 1.41{\rm Lu} - 0.214{\rm Fc} + 0.041{\rm Ad} - ...
0
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0answers
10 views

Interaction between percentage and population size in a regression

Assume I have a regression type model. Are their any statistical and/or substantial reasons NOT to include a two-way interaction which consist of a percentage and the corresponding population size. ...
0
votes
1answer
35 views

Hypothesis Testing using dichotomous and 7-point Likert scale

I am working on testing the following hypothesis: H1: People who are worried about their health will consume yogurt H0: People who are worried about their health will not consume yogurt I have ...
3
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0answers
27 views

Partial regression plots vs scatter plots for checking linearity

In a multiple linear regression analysis, what is the most suitable plot for checking linearity? I have seen a number of examples that use scatterplots as a preliminary test to use a linear model. ...
0
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0answers
31 views

$R^2$ equal square of sample correlation [duplicate]

I?m having a hard time proving that $R^2$ is equal to the square of the sample correlation between $Y$ and $\hat{Y}$. Every book I search tells me that's very easy, like verbeek. They just state that ...
0
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0answers
26 views

F test to compare regression coefficients across different groups, using R

Imagine the following type of dataset: I have a dependent variable Y, two independent variables X and Z, and a variable that can separate the dataset in two smaller datasets. I estimated 2 ...
0
votes
1answer
23 views

correct use of Negative Binomial with a Geometric distribution in a mixed model (glmmPQL)

I am trying to fit a NB GLMM with a gemoetric distribution. I have come across very little information on this form of regression. And would like some pointers/reasurance. some literature is ...
0
votes
1answer
21 views

Interaction model significant in multiple linear regression

This question is not about interaction effect, but about interaction model in Hierarchical Linear Regression. I have 1 DV and 5 IVs. I want to see which of the IVs is significant predictor of DV. ...
0
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0answers
10 views

split file in weka

I want to run a logistic regression were the file is split on a certain value, namely key (major and minor) and I want to see if the other values are able to predict the ranking of a song. But I have ...
0
votes
1answer
52 views

How to determine which variable or combination of the variables are affecting to the predictor variable?

I have one dependent variable name as "win ration" of the deal contested and more than 30 independent variables, all are categorical variable name as role of the customer, geo, region, and 27 ...
1
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1answer
42 views

Interpreting orthogonality

In a multiple partial linear regression setting, the book I'm reading has this sentence: «As a consequence of the fact that residual are orthogonal to explanatory variables, the 'cleaned' variables ...
0
votes
1answer
19 views

model specification problem

I have the following model that I would like to rebuild: $Y_{i,t}=a+bx_{i,t}+cx_{i,t-1}+e_{i,t}$ I' am wondering now whether this is the same as the model above: $Y_{i,t}=a+ d\Delta ...
2
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0answers
27 views

What kind of analysis gives you the statement "If you DONT reach X amount by time T, then your chances go down by P percentage?

I am trying to model growth for data I have regarding downloads of applications. I would like to make a statement, if you "DONT reach X amount of downloads by time T, then your chances of reaching 15 ...
0
votes
1answer
25 views

Which predictors to include in multiple regression where predictors are more than number of samples?

I have 3000 predictors (biological measurements) and 200 samples (weight), and would like to build a linear multiple regression model. How do I select which predictors to include in the regression ...
0
votes
0answers
27 views

How can I use the sufficient statistics (variances, covariances, means) to estimate a linear regression model in R?

My question is simple: is there a function in R which estimates the linear regresion model in a similar fashion as lm, but only ...
0
votes
0answers
43 views

Multiple regression analysis

I have a data set based on 14 field sites, the dependent variable I am investigating is count data recorded at each site (on 3-5 visits). The independent variables (I have around 45) are fixed at ...
0
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0answers
25 views

Estimate linear regression using items randomly selected from an item pool

I am asking this question against the background of a linear regression with single predicted variable $Y$ and multiple predictors $X$. $X$ comes from a survey using an "item pool" which suggests that ...
1
vote
1answer
18 views

Assumptions of two way anova

Please tell me what the actual assumptions of a two way anova are. I read somewhere that this being similar to multiple regression, the only assumption is that the residuals are to be normally ...
0
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0answers
10 views

Mediation and moderation in labeling

So I'm looking at student stigma affecting self-esteem. The overall idea is that stigma affects student achievement through the mediator self-esteem, so I will do multiple regressions and test for ...
0
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0answers
35 views

Neural-Net style pattern recognition with an unknown/varying number of inputs?

Say for example I had a weighted graph such that each node had an associated value. The nodes' values are given by some function of the edge weights and the number of edges as well as the node's ...
0
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0answers
22 views

Multivariate multiple moderated regression

My Dissertation analysis method involves a Multivariate multiple moderated regression. Where I have 4 Dependent Variables (DVs) and 4 Independent Variables (IVs). My model 1 is testing main effects ...
6
votes
1answer
120 views

Follow-up question: When should you center your data & when should you standardize?

I have a follow up question to MånsT's reply to the "When should you center your data & when should you standardize"-question. ( I cannot leave a comment as I am below the magic "50 reputation".) ...
0
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0answers
27 views

How to use factors (from CFA) as independent variable in Regression Analysis

I calculated 4 factors as latent constructs in a Confirmatory Factor Analysis (I use AMOS). Now I am wondering if it is possible to extract some kind of a factor score like I know it from Exploratory ...
2
votes
1answer
35 views

Non normal residuals in multiple regression

I used height, weight, gender and age to regress on BMR (basal metabolic rate) and obtained the following qq plot of residuals I then regressed the above variables with log BMR and obtained the ...
2
votes
0answers
33 views

What is the best way to simulate data for a linear regression model?

I am concerned with simulating data for a linear regression model. I need to control the means, variances, and correlations (covariances) between the predictors and the criterion variable. In ...
0
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0answers
13 views

Identifying the important regressor

In a multiple regression model is the independent variable with the largest weight (coefficient), the one that expains the dependent variable the most?
0
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0answers
22 views

Multicollinearity

In a regression model with dummy variables, how does one check for intearction between the dummy variable and the independent variables?Wouldn't there be problem of multicollinearity when such ...
1
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0answers
5 views

How to calculate model residuals from MCMCregress [migrated]

I'm doing classwork using Bayesian inference. For this, I'm using the MCMCregress function, from MCMCpack. The problem comes ...
0
votes
1answer
14 views

Interpretation of two indexes Interaction Term

Respected Fellows. I will thankful if someone help me to explain my model results.my model is as follows. Yit=αPFit+βPSit+δ (PF*PS) it+εit Where Y is GDP per capita PF=Political Freedom Index ranges ...
0
votes
1answer
32 views

Specifying lag in `dlnm` when passing arguments to `crossbasis`

I am using the dlnm package to build a finite distribute lag linear model. I intend on testing the model-fit based on various lag levels to assess which lag is ...
1
vote
1answer
54 views

Estimation of regression with autocorrelated errors

In a book it is written that, In regression work we typically assume that the observational errors are pairwise uncorrelated. But in most time series data , the successive residuals have tendency to ...
0
votes
2answers
28 views

Overall Significance vs. Individual Variable Significance in Mutliple Regression

I'm running a statistical analysis for work in which I'm trying to determine which (if any) key economic indicators influence our sales. Here is the summary data that I'm getting when I run a ...
1
vote
1answer
59 views

Cook's Distance

The formula of Cook's distance is $$D_i=\frac{(\hat Y-\hat Y(i))^{\prime}(\hat Y-\hat Y(i))}{p\times MSE}$$ where, $\hat Y$ is the prediction from the full regression model and $\hat Y$ is a ...
2
votes
2answers
85 views

Capturing Seasonality in Multiple Regression for daily data

I have a daily sales data for a product which is highly seasonal. I want to capture the seasonality in the regression model. How I can do it? I have read that if you have quarterly or monthly data, in ...
0
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2answers
32 views

Dealing with Categorical variables in Multiple Regression

I have a data having 2 continuous and 4 categorical variables. Each categorical variable has 3 levels. I want to know how to include the variables in the model. I am using SPSS Variables: Sales - ...
1
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0answers
7 views

Use of multiple regression for data on 20 countries representing nearly the whole population

I have operational expenditure data for 20 countries (representing 90% of the whole population) which I want to compare with other variables from the countries (e.g. GDP, Population etc). Do I still ...