Tagged Questions

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

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2answers
29 views

How can I get more precise regression tree?

I am a complete newbie to regression trees so maybe I am not understanding it properly. I got the following tree from my analysis (function tree() from R package ...
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1answer
46 views

What is the distribution of the conditional mean E(Y|X) in a multiple regression?

Suppose the model is $$ Y = b_0 + b_1X_1 + b_2X_2 + b_3D + b_4X_1D + e \\ e \sim\mathcal N(0, \sigma^2) $$ Where $D$ is a categorical variable. $$ E(Y|X_1, X_2, D=1) \sim\mathcal ?? \\ E(Y|X_1, ...
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1answer
26 views

Why can't we add all the individual Pearson's $r$'s in a multiple regression and calculate $R^2$ based on this sum?

Why can't we add all the individual Pearson's $r$'s in a multiple regression and calculate $R^2$ based on this sum? Is there an easy mathematical explanation to this as $r^2$ is squared and don't add ...
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1answer
25 views

What is the relation between multiple-regression and pearson's r?

What is the relation between these two, not $r^2$, but Pearson's $r$ and multiple $r$?
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1answer
23 views

Determine where hazards starts to increase for a continuous variable

I'm interested in a continuous variable, namely blood pressure. The higher the blood pressure, the greater the risk of heart attack and stroke. However, observational data frequently report that also ...
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1answer
8 views

Citation for IV coefficient sign change with inclusion of interaction term

I have a two step regression model where I entered my three IVs in step 1 and one interaction in step 2. One of the IVs in the interaction has a positive coefficient in the first step and then a ...
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0answers
16 views

Why does Frisch-Waugh produce inconsistent estimates with Weighted Least Squares?

Frisch-Waugh's theorem states that in the setup $Y = X^T \beta $, where $\beta = [\beta_1,\beta_2]^T$, $X = [X_1, X_2]$, $\hat{\beta}_2$ obtained from the multiple regression is the same as that ...
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0answers
9 views

Assumptions on a multiple linear regression model and elastic net

I am interested in using elastic net regression in place of an multiple linear regression. I know when you perform a multiple linear regression you should check the assumptions such making sure the ...
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0answers
33 views

Should I use stationarity test before OLS regression

I need to know if conducting a stationarity test on the variables, such as the Dickey-Fuller test, is important before doing any regression like OLS? if so, if the variable is stationary after ...
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0answers
10 views

Substantial changes in significance level when adding more variables to the model [duplicate]

I have a multiple regression model. When I add one more independent variable to the model the significance level of two of my original independent variables suddenly get insignificant. How come? All ...
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0answers
15 views

Regression to chose questions which better correlate with a 10 points likert like score

We have a survey with several questions with 5 likert scale points and we would like to compare the answers to those of another likert like question with 10 points. The approach we thought of is a ...
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0answers
18 views

A reduced regression in SAS [on hold]

I seek your help in modeling a reduced regression in SAS like the following: $Y_i+0.1X_{i1}-0.4X_{i2}=\beta_0+\beta_3X_{i3}+\beta_4X_{i4}+e_i$. The full model is ...
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0answers
13 views

Multiple Reg with 2 Independent Variables that are Correlated - Orthogonalizing the IV's

I have two Ind. V's, $x_1$ and $x_2$. They are slightly correlated with eachother. $x_1$ explains a significant portion of $y$'s variability. Rather than just modeling $y = \beta_0 +\beta_1 x_1 ...
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0answers
23 views

Possible to code contrasts comparing each level to grand mean with no reference category?

I'm working on a health care outcome regression model using the deviation contrast scheme described on the UCLA SAS help page here for a collection of dichotomous predictor variables measuring medical ...
3
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1answer
43 views

test interactions for multiple regression with many predictor variables

I have a data set with around 25 predictor variables. If I am planning to build multi-regression model against this data set. What are the general approaches to test the interactions of these ...
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1answer
36 views

Number of possible statistical test can be used on the observation data.

I am working on research paper for diagnosis of cancer. List of Known prognostic factors Age of patient Size of tumor Grade of tumor Lymphnode involvement and list of Unknown factors which are ...
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0answers
41 views

Linear model / models analysis

Above are three plots of the Linear model I am trying to analyze. The first one is a basic plot of the linear data: ...
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1answer
44 views

Standardized coefficients for linear models with numeric and factor variables in multiple linear regression using scale() function in R

I have on question regarding standardized coefficients (beta) in linear models. I have already asked one question here. From the answers I assume that I should use R's ...
0
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1answer
54 views

When to use bootstapping in regression analyses?

When I run a regression analysis in SPSS, one of my predictor variables just fails to reach significance, p = .06. When I apply bootstrapping, the output tells me the predictor has a significant ...
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1answer
10 views

Survey analysis: relationship between one discrete outcome variable and multiple categorical and ordered categorical variables

I have a data set that is the result of a survey. The survey asks the respondents to name 5 people in their community whom they turn to for advice. It then goes to these 5 people and asks the same. I ...
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0answers
26 views

Analysis of a longitudinal study where interventions are received at different time points

I have a data set of university students. The university has 8 different assisting programs, mostly like scholarships, for needy students to help them concentrate on their studies. Since it costs a ...
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0answers
30 views

Multivariate regression with categorical response variables

Explanation of Data: I started with a data set where each user belong a specific group and their contribution to different domains. After multiple pivots and pre-processing attempts, I got my data in ...
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0answers
15 views

Getting estimates of hospital specific stroke admissions data

I am analysing a small data set on stroke process of care gathered from public sources but don't have access to hospital specific emergency stroke admissions over a period of time data except for ...
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0answers
49 views

Selecting a multiple linear regression model with categorical variables

I am trying to analyze the Berkeley Guidance Study to practice multiple regression models, which has 10 continuous variables, 1 categorical variable (with two categories) and the response variable. ...
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1answer
19 views

Determining amount of change in correlated variables

Say I have 3 independent variables (x1..x3), all highly correlated with a dependent (Y). I'm looking to determine if x1 changes by a certain amount, how much Y would expected to change. Also, looking ...
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1answer
29 views

Modelling interaction

How does adding interaction term in the model adjust for it or why do we need to add interaction? I am working on logistic regression model with treatment and race as predictors. I have added ...
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0answers
20 views

How do I choose the optimal number of lags?

I am making a model (multiple regression) that predicts credit growth. Many of the independent variables are leading indicators and should therefore be lagged. How do I choose the optimal number of ...
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1answer
29 views

Oaxaca Decomposition: Unexplained Constant

I am doing an Oaxaca decomposition of the Log Wage Differential between Whites and non-Whites. I would like to find out if there is any interpretation for the constant term under the unexplained ...
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1answer
20 views

Finding Bias$(s^2)$ in incorrect linear model

I am unable to find the bias of the sample variance estimator in this problem. Unfortunately I keep coming up with Question: Suppose that the true linear model is $y = X_1\beta_1 + X_2\beta_2 + ...
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2answers
37 views

Magnitude of standardized coefficients (beta) in multiple linear regression

Being aware of that article, I am curious about the question how big standardized coefficients can get. I had a discussion with my professor about that issue and she was arguing standardized ...
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0answers
6 views

Estimate standardized coefficients (beta) using lm.beta() from package 'QuantPsyc' [migrated]

I want to estimate the standardized coefficients (beta) from a multiple linear regression object using lm() function in R. I use the lm.beta() function from the package 'QuantPsyc', but I do get a ...
1
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1answer
42 views

I am having trouble understanding (and implementing) logistic regression for classifying into three classes

(For reference, i am using Kevin P Murphy's Book "Machine Learning: A Probabilistic Perspective" and implementing with MATLAN - without any toolboxes) I have a dataset with 392 samples (rows), each ...
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0answers
10 views

Help required in controlling for socioeconomic factors when mapping travel behavior

Background I have cleaned disaggregate travel data down to a household level (of about 75% of households) and socio economic data aggregated into 100-200 household blocks. What I'm wanting to do is ...
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0answers
34 views

questions on characterizing a variable into ordered, categorical or continuous

When building the regression models, some independent variables are of the following type x={1, 2, -100.1, 200.1, 300, 0, 0, 0, 0, 4000} If there exists an ...
2
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1answer
39 views

Interpretation of betas when there are multiple categorical variables

I understand the concept that $\hat\beta_0$ is the mean for when the categorical variable is equal to 0 (or is the reference group), giving the end interpretation that the regression coefficient is ...
0
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0answers
19 views

How to compute F-statistics for each features of regression models in glmnet?

I have learned lot's of Lasso regression models(20000) using glmnet. I need to compute somehow test statistics for each features of models. like F-statistics,... Can I do this using bootstrapping ? ...
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1answer
30 views

build model with complicated types of feature variables

I have been asked to build a model to predict a life span of a material based on a couple of features. The features can be classed into the following categories: 1) The feature variables just have 0 ...
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0answers
14 views

How to share weights of between regression models when you learning them simultaneously?

I have many phenomenons which I want to model them as lasso regression problem. every phenomenon have it's own distinct features set. but for some phenomenons, the subset of features set are the ...
1
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1answer
23 views

Confused Beginner Question: Multiple simultaneous tests and signal pollution

The best way for me to explain the problem might be to just give an instance of our data and the type of test/conclusion I am attempting to draw. Unfortunately as the title suggests, my understanding ...
2
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1answer
22 views

Which mean to use for centering variables when sample definition varies

I am centering variables that enter interaction terms in my linear regression. To check the robustness of my results, I exclude certain cases from the original sample, and re-run the regression ...
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0answers
7 views

How to fit a series into another one so that their mutual information is minimized?

I am building a multivariate model of an output series. I have many series-candidates for inputs. I want to select the inputs based on the mutual information between these inputs and the output. My ...
0
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1answer
30 views

Inflation of Adjusted R2

Consider the case of a multiple regression model, with about 10 regressor and very few observations (about 15). I have to choose 10 out of 20 available regressors, to be included in the model. In many ...
1
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1answer
42 views

What is the benefit of knowing the F statistic in multiple linear regression?

One of the basic figures you get when running multiple linear regression using almost any off-the-shelf software is the F statistics. However, I cannot recall one situation, where the F value was low ...
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0answers
40 views

Can factor analysis improve the fit of a predictive regression model?

My company is working with a client who have built a logistic regression model to predict whether kids with psychiatric disorders will successfully complete a State intervention program (Yes or No). ...
2
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2answers
43 views

Multiple logistic regression and public behavior

I'm trying to develop a model to forecast the behavior of the public... specifically, in horse racing. Most models in horse racing use whether or not the horse won as the dependent variable and then ...
1
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2answers
59 views

Controlling for age in multiple regression

I am a little stuck on what how to implement and interpret a multiple regression while controlling for age. I am interested in seeing if there is a positive relationship between depression and use ...
0
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0answers
34 views

Regression where Dependent Variable Ranges in Value

I need to perform regression analysis, but my dependent variable doesn't have a fixed value, but is in a range. So, for example, one of my dependent variables might have a value of $51\pm 3$, another ...
1
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1answer
91 views

Summarizing and plotting several combined relationships with LMER

I want to see if there is a significant relationship between predictor and value. I've measured these two variables in 6 different conditions (not a full 3 x 3 design because feature1 and feature2 ...
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2answers
96 views

How to perform residual analysis for binary/dichotomous independent predictors in linear regression?

I am performing the multiple linear regression below in R to predict returns on fund managed. reg <- lm(formula=RET~GRI+SAT+MBA+AGE+TEN, data=rawdata) Here ...
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0answers
31 views

Correlation and regression giving opposite results

I have two variables with ordinal, not normally distributed data. A Sperman's correlation coefficient indicates a negative correlation. After, I performed a multinomial regression which indicates a ...