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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11 views

Forecast using multivariate multiple linear regression using R for multiple dependent variables

I'm trying to do predict using multiple linear regression in R. I have been able to do the multiple regression bit, by converting raw data to data table. However, when i'm trying to use predict ...
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2answers
34 views

What are the major differences between the parameter estimation of a simple linear regression vs multiple?

This is the standard technique that I have used to calculate the parameter of a single linear regression problem with one independent variable. How does the parameter estimation problem differ in ...
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0answers
25 views

Interpreting coefficients of Regression Model (Mincer Model)

Hi all, I am an undergraduate student who is currently doing an assignment. I am now facing a few problems which are:- 1) Age is usually a positive return to wage, but in my regression output, ...
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2answers
32 views

Does the actual coverage of a 95% CI on $R^2$ get closer to nominal coverage with larger sample size?

If the answer is "it depends", what does it depend on? Does convergence depend on the ratio of predictor variables to sample size, or the size of $R^2$, or something else? I am mainly interested in ...
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4answers
67 views

How to deal with curvature in residuals plot

I am trying to do a multiple linear regression in R but am having some problems. I have a set up where I am trying to develop a multiple linear regression model for one variable (y) using six other ...
0
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1answer
37 views

What do the coefficients of the crossproduct of regression mean?

How can I interpret the coefficients of the crossproduct of each of the following codes? What do they mean? How can I deduce that they correspond to our expectation? ...
0
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1answer
15 views

How to interpret results if a reference category of a categorical variable in multivariable logistic regression is not significant?

I am trying to do a multivariable logistic regression and using a normal binomial logistic regression, using binomial variable X (coded ...
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0answers
15 views

How to graph interaction effects for panel data

I have a pretty generic question which I am guessing could be relevant to many social scientists who deal with panel data sets. What are the best practices for making graphs about interaction effects. ...
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0answers
14 views

Dynamic Regression

Problem Suppose that a typical firm determines its level of stocks $H_t$, in accordance with the following rule: $H_t - H_{t-1} = \lambda (H^*_t - H_{t-1}) + \epsilon _t$ where $\epsilon _t$ is a ...
3
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3answers
65 views

What problems do non-normality in predictor variables cause for a multiple regression analysis?

I am talking about a situation in which I have several continuous predictor variables predicting a continuous outcome. One of the predictors has a very non-normal distribution and has some wild ...
0
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0answers
35 views

Identifiability in linear regression

If we have a generative model: $X_2=X_1a_1+\varepsilon$, where $\varepsilon \sim \mathcal{N}(0,\sigma_2^2)$, do we have $X_1=X_2a_2+\varepsilon '$, where $\varepsilon \sim \mathcal{N}(0,\sigma_1^2)$ ...
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0answers
29 views

Can Pearson correlation be used as a measure of fit?

In the context of multiple linear regression, is it acceptable to use Pearson correlation to discriminate how well a model fits a data set? Let's say that I have some experimental values that come ...
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0answers
17 views

Compare the marginal effect for a dummy variable with a continuous variable from a probit model

I use probit model for one regression which consists one independent dummy variable that captures whether the firm is unionized or not. I also estimate the same probit model instead of consisting ...
7
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1answer
333 views

What is the difference between multiple regression & mutivariate regression?

I have data on GDP growth as a dependent variable and growth in main production sectors of Pakistan such as mining, electricity, communication, manufacturing and electricity. I am supposed to run a ...
2
votes
1answer
62 views

How to compare whether the coefficients of two independent variables statistically different from each other?

If I have two independent variables and they are dummy variable along with other independent variables and I run a linear probability model, I want to compare whether the coefficients of two dummy ...
0
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0answers
23 views

Joint k-linear regressions

I would like to learn simultaneously $k$ linear maps $\{\phi_0, \dots ,\phi_{k-1} \}$ at the same time: $min \sum_{i=0}^{k-1} \sum_{j=i+1}^{k-1}||X_i \phi_i - X_j \phi_j||_2^{2}$, such that ...
1
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1answer
21 views

When using higher order terms in multivariable regression what is the effect on the P-value

I have a large dataset, lets say 500 lines of data. As a quick workaround to higher order regression I've made educated guesses about what higher order terms I would expect in my regression equation. ...
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0answers
31 views

What is PRINCIPAL HESSAIN Direction Model, how and where can I use it?

I'm a M.Tech student going through my academic project-work, here I have asked to develop a optimal design and a best equation to fit the data for a Leaching, Solvent extraction and Electrowinning ...
0
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1answer
14 views

F-test formula under robust standard error

I am attempting to write a program that will (among other things) use the F-test in multivariate regression under standard robust errors. I am having trouble finding a specific formula for the ...
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1answer
23 views

Choosing a regression model based on missing values

I'm trying to predict weight change with an intervention from baseline variables. Literature search yields suggests several predictors. Univariate analyses with weight change as dependent and baseline ...
2
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2answers
45 views

Why do both the VIF and tolerance statistics exist, when the latter is just the reciprocal of the former?

Is taking the reciprocal helpful in some way, or is it just a matter of historical accident that there came to be two terms to describe the same thing? (From the Wikipedia page.)
2
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1answer
38 views

How to present a large dataset of polynomial multivariable regression in a useful format

I've produced a large dataset of results from 3 variable inputs. eg: x1, x2, x3 -> y y(x1,x2,x3) I've gone over the problem logically and it was clear the problem was non linear. To this end I've ...
0
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1answer
29 views

Considering correlation of independent variables in regression model

I have one dependent variable C and four independent variables: S SD ...
0
votes
1answer
31 views

Do dummy variables count as independent variables when calculating degrees of freedom in a multiple regression?

The degrees of freedom in a multiple regression equals N−k−1, where k is the number of variables. Does k include dummy variables? For example, I have the model: ...
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0answers
28 views

using stepAIC of MASS package to select variables with a significance level of 5% in R project

First of all, sorry i am new about this and any helps are really welcome. I am reading a reaserch paper where the authors report: Stepwise forward regression (Zar 1996) was used to select the most ...
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0answers
8 views

Evaluating relative importance for a group of independent variables

I have done a multiple regression analysis of a group of design variables for a system I am analyzing. From this I determined the standardized regression coefficients. All of the variables fall into ...
2
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1answer
25 views

Test of significance of multiple proportions in two groups

I have a dataset of two genetically different cell types, "A" and "B", and each of them can have four different morphologies, let's say "spiky cell", "elongated cell", "round cell", "triangular cell". ...
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2answers
25 views

When doing a t-test for the significance of a regression coefficient, why is the degrees of freedom n - predictors - 1?

I read at http://www.unesco.org/webworld/idams/advguide/Chapt5_2.htm that this was the degrees of freedom I should use, but I don't understand why. My understanding was that t-tests generally had n-1 ...
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0answers
33 views

What does it mean to explain variance?

In particular, I am wondering why we have this concept Multiple R (which I can understand as the correlation between observed and predicted scores in multiple regression), and then a separate concept ...
2
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1answer
41 views

What's the difference between regression coefficients and partial regression coefficients?

I've read here that When the independent variables are pairwise orthogonal, the effect of each of them in the regression is assessed by computing the slope of the regression between this ...
3
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3answers
244 views

Is this the correct way to interpret regression coefficients?

Say I have some data on people where I have a measure of their general health (some score out of 1000), the number of apples they eat in a year, and the number of oranges they eat in a year. Then I ...
0
votes
1answer
54 views

Extracting the model p-value for a multiple regression in R

When fitting multiple variables to one outcome via the lm() function in R, summary(lm) gives me the p-values for individual ...
0
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0answers
18 views

Is it correct to combine PCA and NMDS axes in a multiple regression?

I am considering to do a multiple regression in which some of the predictive variables are PCA (principal components) axes whereas others are NMDS (nonmetric muliple dimension scaling) axes. I would ...
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0answers
34 views

Random model selection and validity of significance tests

Suppose we have some data, $\{y_i, x_{1i}, \dots, x_{ki}\}_{i=1}^n$ and we want to build a linear model of the form $y_i = \beta_0 + \beta_{1'i}x_{1'i} + \dots + \beta_{k'i}x_{k'i} + \epsilon_i$, ...
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0answers
23 views

When including a linear interaction between two continuous predictors, should one generally also include quadratic predictors?

Suppose I am fitting a linear model, and I have two continuous predictors x1 and x2. I think that they might interact, so I add ...
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1answer
51 views

ISPSS: Cross-sectional time series analysis

I am trying to run a multiple regression in SPSS. I am using panel data with 4 independent variables. Of these, one is a dummy variable. Can someone please guide me through the process or give me ...
0
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1answer
33 views

Correlation and regression [duplicate]

Can there be negative correlation but the regression line has a positive change when there is an increase in the independent variable?
1
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1answer
31 views

How to conduct regression analysis on ordinal variables in SPSS?

My data basically includes a number of ordinal (and some nominal) variables on perceptions of volunteers. I essentially want to see whether perceived personal benefit from volunteering (based on a ...
1
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0answers
48 views

What is the formula of correlation coefficient against 3 or more variables?

This is the formula for calculating the coefficient of correlation between a single subject value ($z$) and two reference variables ($x$ and $y$). The question is how to expand it to cases when ...
0
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0answers
9 views

mlogit query with multiple options: response rate not good for third variable

I am stuck with one query on mlogit. I have three options (0,1,2) for prediction of probabilities. The model equation is: ...
4
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3answers
357 views

Why is polynomial regression considered a special case of multiple linear regression?

If polynomial regression models nonlinear relationships, how can it be considered a special case of multiple linear regression? Wikipedia notes that "Although polynomial regression fits a nonlinear ...
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0answers
21 views

how can i use regression model selection technique and to carryout ANOVA for calculated data [duplicate]

how can i use regression model selection technique and to carryout ANOVA for calculated data I have problem regarding to know , what kind of relationship is excised between parameters to produce a ...
0
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1answer
53 views

R: Setting an F-statistic to determine variables for a multiple linear regression model

I am trying to understand the steps behind the linear regression process. I already have a linear model like: lmodel1 <- lm(y~x1+x2+x3, data=dataset) for which ...
2
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4answers
269 views

Improving a linear regression: Add predictors or change model?

I am trying to model a time series variable $Y_{t}$ with $4$ physical predictor variables. I used the following linear regression: ...
0
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0answers
16 views

Multivariate multiple regression in SAS [migrated]

Suppose I want perform a multivariate multiple regression analysis and test (using a single test) the hypothesis, that the regression parameters for two explanatory variables are 0. In ...
4
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1answer
53 views

Residual Vs. Fitted Plot with Outliers

I have a model relating fuel consumption to other vehicle parameters, which produces the following Residuals Vs. Fitted plot. My Question: Is the skew to the right simply an indication of outliers ...
1
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1answer
53 views

R: multiple linear regression model and prediction model

Starting from a linear model1 = lm(temp~alt+sdist) i need to develop a prediction model, where new data will come in hand and predictions about ...
4
votes
3answers
92 views

Selecting most important variable based on individual p-value vs. partial $R^2$

I'm trying to solve a problem where the goal is to find an association between children's cortisol values (y) against their mother's weekly cortisol averages (...
0
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0answers
27 views

Sequential Sum of Squares, degree of freedom when number of variables greater than number of samples

I would like to use the Sequential Sum of Squares test. But the degree of freedom for the denominator is (n - p - 1), where n = number of samples, and p = number of variables in the full model. What ...
2
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0answers
22 views

multiple linear regression with normalization - how to get non-scaled full covariance matrix

I am doing a quite complicated multiple regression modelling in physics and have a problem how to got back to covariance matrix for non-normalized parameters. I don't know how to calculate the error ...