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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7 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
191 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
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1answer
55 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. ...
0
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0answers
27 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
11 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 ...
1
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1answer
22 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
43 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.)
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1answer
33 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
28 views

Considering correlation of independent variables in regression model

I have one dependent variable C and four independent variables: S SD ...
0
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1answer
27 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: ...
0
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0answers
21 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
votes
1answer
23 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". ...
1
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2answers
24 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 ...
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 ...
1
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1answer
32 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
239 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
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1answer
51 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
16 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 ...
0
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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 $y_i = \beta_0 + \beta_{1'i}x_{1'i} + \dots + \beta_{k'i}x_{k'i} + \epsilon_i$, ...
3
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0answers
21 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
47 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
30 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
47 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
8 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
353 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 ...
0
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0answers
20 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
51 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
262 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
votes
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
votes
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
52 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
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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
21 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 ...
-1
votes
1answer
25 views

how to do category regression

I have a set of data which contains students first term gpa, final gpa, their age, race, state and so on, I need to predict student's final gpa based on the others, my problem is how to convert race ...
0
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0answers
27 views

Multivariate grouped data in R

I have a dataset of gambling expenditure, income, verbal reasoning test scores and gender. I tried two different methods for fitting a linear regression: ...
6
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2answers
268 views

Is it inappropriate to call multiple regression analysis 'correlational'?

I recently received a review back for a paper in which I referred to some previous studies as 'correlational' where they used multiple regression to analyze some population data and make biological ...
3
votes
1answer
43 views

How can you have significant correlations and insignificant coefficients?

I'm a psychology graduate, so I admit that statistics do not come naturally to me. However, I find them fascinating nonetheless. At the moment i'm struggling with regressions, or specifically in this ...
0
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0answers
19 views

handling multicollinearity by backwards regression and omitted variable bias

Suppose I try to estimate a production function as follows: $logY=b_0+b1*logX_1+b_2*logX_2+b_{11}*(logX_1)^2+b_{22}*(logX_2)^2+b_{12}*(logX_1)*(logX_2)+u$, where $Y$ is the output, $X_1$, $X_2$ are ...
2
votes
1answer
91 views

What type of multivariate linear regression is this?

I'm trying to reproduce a result from a book (see bottom) and it doesn't work. I would like to do some further readings about this method but he doesn't specifically give the method other than a ...
5
votes
0answers
35 views

Can (should?) regularization techniques be used in a random effects model?

By regularization techniques I'm referring to lasso, ridge regression, elastic net and the like. Consider a predictive model on health care data containing demographic and diagnosis data where length ...
3
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3answers
132 views

Multiple Regression and number of parameters to include for a learning algorithm

I am quite new to Machine Learning and come from a computing background. I have a quite big set of features (~50) with about 4k observations. Is it correct thinking to include all of them in a ...
4
votes
2answers
90 views

How to describe or visualize a multiple linear regression model

I'm trying to fit a multiple linear regression model to my data with couple of input parameters, say 3. \begin{align} F(x) &= Ax_1 + Bx_2 + Cx_3 + d \tag{i} \\ &\text{or} \\ F(x) &= ...
0
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1answer
24 views

What variables do I keep in the model? multiple linear regression

What do I do when none of the predictor variables are significant? All the p-values are greater than the significance level of 0.05.
2
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1answer
53 views

What is the purpose of precision variables?

Why do we need to include precision variables in a regression model (i.e., a variable that is associated with the outcome but not the predictor of interest)?
0
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1answer
38 views

least trimmed squared for regression

i'm new in statistics. hope you can help me on the following: i want to use least trimmed squared (LTS) for regression. below is the coding in R: ...