Regression that includes two or more non-constant independent variables.

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16 views

Relationship between 3 variables confused

I am working on analyzing some data for my master's thesis, and I am not exactly sure how to interpret my results. Let's call my variables A, B, and C. Variable A is negatively correlated with ...
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1answer
34 views

What is the “partial” in partial least squares methods?

In partial least squares regression (PLSR) or partial least squares structural equation modelling (PLS-SEM), what does the term "partial" refer to?
3
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2answers
35 views

Generate fake data consistent with adjusted R^2 pattern

Is it possible to specify a vector of adjusted $R^2$ values (or any other measure like AIC, BIC, $C_p$) for the set of all possible models in a data set, and then generate data that is consistent with ...
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21 views

Bayesian Multivariate Linear Regression or Machine Learning Methods

I am trying to apply some Machine Learning concepts to time series forecasting, where normally I would use more traditional statistical methods. For example, say I have a sample dataset with two ...
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3answers
157 views

Small data set and linear regression

If I have a small data set (30 samples) am I more likely to obtain a statistically significant result? From my understanding if there are any relationships within the data set then they will be over ...
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2answers
57 views

Analyzing residuals in logistic regression

Greetings statistics experts, I am having a try with the kaggle titanic dataset and am wondering what to do with the residuals after fitting models. In the case of linear regression you can look at a ...
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18 views

Assessing Multiple Regression Normality

Normal distribution in data is one of the assumptions in multiple regression analysis. In the situation where the Skewness test, Kurtosis and Q-Q plot showed the evidence of normally distributed ...
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1answer
20 views

Help with dummy variables

Can you please help me with 2 questions (both to do with dummy variables) - 1) If I have 2 sets of nominal variables (eg ethnicity [white, Indian, African] and smoking status [current smoker, ...
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18 views

How can the relative importance of a categorical variable in a linear regression model be determined?

A simple example can be seen here:http://www.ats.ucla.edu/stat/spss/output/reg_spss.htm Gender is a dummy coded variable. I completely understand how to interpret this variable. I cannot use the ...
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1answer
64 views

How to deal with non-normally distributed residuals?

I'm fitting a multiple linear regression model. I've read that the residuals of my regression need to be normally distributed in order for the p and t values to be accurate. Now my residuals (see ...
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1answer
10 views

Can anyone give me some clarity on Q2 where PLSR is concerned?

Can someone describe to me in laymen terms what Q2 values mean with regards to PLSR I understand that it is a cross validation number, but i have no idea what it is saying. only that the model is ...
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0answers
18 views

finding relationships between variables in dataset [on hold]

I have a large project data set, which includes numeric values like dollar amounts, and non numeric quantities like country codes, purpose codes etc. I want to find relationships between the ...
2
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1answer
39 views

Multiple regression with correlated variables

I am trying to do multiple regression analysis of a continuous health variable (yval) keeping age, gender, height (cm), weight (kg) and waist (cm) as predictor variables for a database of about 7000 ...
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2answers
69 views

What criteria tell us that the prediction of a model is reliable

What criteria can be used to tell whether the prediction of a model will be more reliable than other specifications. Background: We have data with $N$ computers. However, prices available only ...
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30 views

Find distribution of Bus arrival time

I am currently working on a problem in my research which can be modeled into the following question: Let's say I have a rich dataset with values for the variable $A$ which is equal to ...
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0answers
30 views

Estimate Probability of being in a time interval

​You arrive at a bus stop in an unfamiliar part of town. Assume that buses arrive at the stop with an unknown (to you) distribution and wait in the bus stop for a few ​minutes. The wait time ...
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0answers
40 views

Prediction based on multiple time series - Python

I have 3 predictors and 1 variable that represents ground truth. They all are linked time series. My purpose is with the 3 predictors to try to forecast the ground truth data. For example : ...
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0answers
9 views

Adding a new factor to an existing factor model for stock returns

Let's assume I have a three factor model of stock returns (Cross-sectional model): $R_i = \alpha + \beta_{1,i} X_1 + \beta_{2,i} X_2 + \beta_{3,i} X_3 + \epsilon_i$ for $i =1,..,N.$ where ...
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26 views

Assesing the explanatory power of predictors, interactions and combination of terms

I have a model with 5 basic predictors and all interactions between the predictors themselves. Something like (I'm simplifying here, in reality I have many more variables): ...
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29 views

How to handle autocorrelated residuals (and independent variables) in multiple regression? [closed]

I am trying to carry out multiple regression for an air pollutant (dependent variable), and weather parameters- wind direction, wind strength, rain, air temperature, relative humidity (independent ...
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1answer
18 views

Test equality of coefficients in separate regressions when populations are not independent

I have three regressions with the same IVs. Equation 1: Y1 = X Equation 2: Y1 = X Equation 3: Y2 = X X is a vector of IVs with B1-B8 coefficients. Equations 2 and 3 are tested on the same ...
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1answer
49 views

Accounting for unknown error in multiple regression?

I have a very naive question about multiple regression and errors...one that isn't addressed here already (Choosing a robust estimator to account for measurement error in dependent variable) I would ...
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1answer
40 views

Selecting variables in multiple linear regression in R

Consider that we have a problem with 4 variables (y, x1, x2 and x3) and we want to do a multiple linear regression model. As we need to know which variables are the most important in the problem, we ...
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1answer
40 views

Do different units of explanatory variables affect p-values?

In multiple linear regression, does including variables with different metering units and thus values very different in dimension/size affect statistical significance/ p-values? In my model, a ...
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2answers
73 views

Should I remove non-significant variables from my regression model

I have run a multiple linear regression using stepwise regression to select the best model, however the best model returned has a non-significant variable. When I remove this the AIC value goes up ...
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0answers
17 views

Migration Flows and Multiple Regression Quadratic Assignment Procedures

I'm a forth year economics student (undergraduate) and last semester I wrote a research paper, with a classmate, in which we analyzed the determinants of interprovincial migration flows in Canada. It ...
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23 views

Searching for the non-zero coefficients in lasso regression using glmnet.

I have to analyze genomic data set: ~ 22 000 of gene expressions for the two groups each of 40 subjects. I have tried different methods to find genes, which are significantly different among two ...
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18 views

Does multiple regression applied to panel data yield the same estimates as pooled OLS?

I'm trying to analyse a large unbalanced panel dataset. First, I simply used multiple linear regression and obtained feasible results (parameter estimates). Later, I was advised to use pooled OLS ...
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1answer
10 views

Multiple Regression study design - questionnaires

If an existing questionnaire does not exist to tap into a construct, is it better to change the instructions of a preexisting measure that isn't quite tapping into the variable of interest to have ...
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22 views

How does turning categorical variables into dummy variables affect ANOVA results?

I'm running a multiple linear regression with (amongst others) several categorical explanatory variables. My categorical variables are factors with several factor levels. For example, variable $x_1$ ...
2
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1answer
23 views

Does robust regression affect contributions to explained variance by the different variables?

I've learned that in multiple linear regresion, parameter estimates as well as R$^2$ are not affected by using robust standard errors, i.e. are the same as resulting from non-robust regression. I now ...
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4answers
228 views

Linear regression - is a model “useless” if $R^2$ is very small?

Given a complex output which depends on many underlying factors, I am given 3 explanatory variables and about 10K data points and the task to assess their impact on the output. The OLS model is very ...
2
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1answer
48 views

how to test the significance of a multivariate, multiple regression model as a whole

I have a dataset with seven dependent variables and three independent variables. Now I want to test the significance of a multivariate regression model as a whole. My model looks like this (using ...
2
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1answer
37 views

Is testing predictors separately theoretically sound?

I am running a regression analysis to understand the effect of several IVs on the transport mode choice of questionnaire respondents. My sample of respondents is of 100, and I have more than 10 ...
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1answer
27 views

Should you t-test variables before putting them in a multiple regression?

We are doing a research project looking at attachment's relationship to trust. We have measured possible confounding factors: age, relationship status and sex. We did t tests (categorical variables: ...
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33 views

Is there a difference between modeling Path Dependence and using a Lagged Dependent Variable?

I am modeling the choice of transport mode of a series of questionnaire respondents at year y. So far, I've resorted on modeling the choice as a function of a ...
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1answer
42 views

Can site be used as a factor in a multiple regression model?

I am studying two sites with different fertility and soil texture. In the model I used the data from both sites. I would like to know if could I could use the site as a factor (variable) in the model? ...
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44 views

Interpretation of output generated by PROCESS macro in SPSS for model with two moderators

I used the PROCESS macro for SPSS from hayes to regress a model where det_mean is the indepedent variable and y_tot the depending variable. I'm testing if this relation is moderated by two variables ...
2
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1answer
64 views

Time-series regression

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 serially ...
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11 views

mat.regress/set.cor [migrated]

I am having a problem with the function mat.regress in the psych package that I was hoping someone would be able to give guidance on. I have a correlation matrix that is [76,76] with the first ...
4
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1answer
37 views

Do you think I should apply a transformation to my independent variables?

I have done a simple linear regression on my two standardized independent variables and standardized dpendent variable. In the residual plot there is a distinct quadratic pattern left after the two ...
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11 views

Largest value in a set with a nearly equal distribution between value +/- 20%?

I am working through a data analysis task in a contract, and trying to build a generalized spreadsheet that can be used for this and similar analysis. I'm tripped up by a requested procedure, and ...
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2answers
151 views

How to get ANOVA table with robust standard errors?

I am running a pooled OLS regression using the plm package in R. Though, my question is more about basic statistics, so I try posting it here first ;) Since my regression results yield ...
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0answers
14 views

Bagging for sparse survey data regression?

A colleague came to me with an idea for training a regression model from a very large but sparse survey data set. In this data set, many variables are available but most respondents only answered a ...
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0answers
13 views

high correlation between IVs, but VIF and tolerance normal?

In a multiple regression analysis: If two variables are correlated by more than .8, but the VIF for each of them are 1.005 and 1.006 and the tolerance numbers .994 and .995, what exactly does this ...
3
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1answer
54 views

What if a transformed variable yields more normal and less heteroskedastic residuals but lower $R^2$?

I am trying to decide whether to use a square root transformed dependent variable in multiple linear regression. Transforming $y$ leads to more normally distributed residuals and also to less ...
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2answers
166 views

Which residuals to analyse when dependent variable is transformed?

I am running a multiple linear regression where the dependent variable is sqrt-transformed. As far as I understand, the residuals from the regression are different from the residuals calculated as ...
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0answers
28 views

Regression sum of squares (SSR) when $\beta_0 = 0$ in multiple linear regression?

I hope this is not a duplicate but I cannot find the answer to this question. In a linear model $$Y_i = \beta_1 X_{i,1} + \dots + \beta_{p-1} X_{i,p-1} + \varepsilon_i, \qquad i = 1, \ldots, n$$ with ...
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9 views

Raw values vs SDS for linear regression?

I have data on age, gender, height, weight and a health variable (call it yvar) which is a continuous variable in the range of 50-150. The age is in the range of 5-15 years (a study of children). I ...
4
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1answer
31 views

Basic - Modelling Two Series, one is an index

I'm trying to model two time series. One is a seasonally adjusted # of new jobs number against and index of business development. Its been a long time since I took econometrics, so I'm hoping ...