Tagged Questions

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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11 views

Dummy variable interpretation [duplicate]

I have a model $$\ln({\rm earnings}) = 2.618656-.0899657{\rm female}+.382019{\rm white}-.2754126 {\rm female}\times{\rm white} $$ Now i know there is gender pay difference with b1 (9%), I also know ...
1
vote
1answer
29 views

Dummy variable interaction regression [duplicate]

I have a model: $$ \ln({\rm earnings}) = a+b_1{\rm female}+b_2{\rm white}+b_3{\rm female}\times{\rm white} $$ ${\rm female}$ and ${\rm white}$ are dummy variables. I have interpreted $b_1$ and $b_2$: ...
0
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2answers
15 views

Testing equality of two X values in quadratic regression

So let's say we have a quadratic relationship between two variables, y and x. Graphically, it is U-shaped. However, there is also a linear component to it, such that the left curve is lower than the ...
1
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0answers
11 views

How to test heteroskedasticity at the independent variable level?

I know how to test the heteroskedasticity of a model's residuals. I am inquiring about how to test for heteroskedasticity for each specific independent variables included in the model. What is the ...
0
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0answers
17 views

Add a quadratic random effect to a nonlinear mixed model?

How can one add a quadratic random effect to a nonlinear mixed effect model? I've been trying to do this with nlmer without luck. Any tips would be greatly appreciated! Here's my starting point that ...
0
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0answers
19 views

Propensity score to match on exposure thats not a treatment

I have two questions on this subject: (1) The literature on propensity score (PS) consistently discusses the ability of PS to balance groups with different treatments. Does PS allow for balancing on ...
0
votes
1answer
15 views

quantile regression with e.g. gamma distribution and log link

I have a basic question about quantile regression (I'm new to it): Why doesn't it seem possible to do a quantile regression with a specified family (e.g. gamma) and link function (e.g. log), as in a ...
4
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3answers
86 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, ...
0
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0answers
12 views

Expand scale bias correction factor (infinite series) [duplicate]

I am trying to expand a scale bias correction factor to 10 to 15 terms but I am spinning my wheels. Too long since engineering school. Here is the series. I have values for $m$ and $T$. ...
6
votes
2answers
222 views

Why is GLM different than an LM with transformed variable

As explained in this course handout (page 1), a linear model can be written in the form: $$ y = \beta_1 x_{1} + \cdots + \beta_p x_{2} + \varepsilon_i$$ , where $y$ is the response variable and ...
2
votes
0answers
21 views

How to use delta method for standard errors of marginal effects?

I am interested in better understanding the delta method for approximating the standard errors of the average marginal effects of a regression model that includes an interaction term. I've looked at ...
2
votes
1answer
61 views

How can I remove multicollinearity from my logistic regression model?

I am working on Sales data. i have binary variable win/loss the opportunities and rest are the activities done by sales force (sales guys) with 40+ variables (different types of activities done for ...
0
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0answers
26 views

What is the difference between Bézier splines and Loess curves?

I'm a bit naive on this topic, and wanted to understand the difference in the mechanics of Bézier splines and Loess curves as curve-fitting methods.
1
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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 ...
0
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0answers
13 views

Hypothesis test of significance using a stratified sample

I am fitting a linear model (OLG) of the form: Y_hat =b0 + b1*x + b2*x*(grp='b') + b3*x*(grp='c') where x=(x1, .., x7) is a vector of continuous predictors, grp is a discrete variable that takes ...
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0answers
14 views

Should I assign numeric values to classes?

I was reading a paper and there was a dataset with 3 distinct classes. So, he assigned 0, 0.5 and 1, respectively to the classes. He used SVR. Then he used a method to find thresholds so it can assign ...
0
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0answers
23 views

Mix of two bivariate distributions (two correlations hidden in data)

We have two metric (continuous) variables, say $X$ and $Y$ and are interested in a correlation between $X$ an $Y$. Actually, a correlation test (Pearson or Spearman) is not significant, i.e. it does ...
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0answers
20 views

Transformations in Simple Linear Regression [duplicate]

Suppose a linear model for Y in a single predictor var, X. If the residuals show a pattern of increasing variance (wrt X), sometimes a transformation of Y, Y'=f(Y) is considered (where f is sq rt, ...
5
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3answers
361 views

Using years when calculating linear regression?

I'm new to statistics, and I'm currently trying to solve an assignment for my course. The assignment is to calculate the linear regression analysis/regression equation for a data set containing ...
0
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0answers
16 views

RANSAC Multivariate Regression

I am using RANSAC as my robust regression method. I saw many examples for a line and a plane but what if there are many independent variables as in multivariate regression. Is there anyway handle ...
0
votes
1answer
27 views

Missing factor levels after logistic regression glm()

I am quite new in the R universe, so please excuse me if the question is too simple.. I would like to perform a logistic regression on a marketing data set (only categorical variables), of the form ...
0
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0answers
34 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 ...
0
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0answers
10 views

Best statistical method to answer relationship - User Participation Groups

I am working with large data set. In the data set we have user participation (some metric), their expert level and group they are belong to. ...
0
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0answers
46 views

weighted likelihood of logistic regression [on hold]

Let $X_{ij}$ matrix np , $Q_{ij}$ and $N_{ij}$ matrices np . $y_i$ is the response $\in$ (0 or 1) , $y_i = binom(1,p_i)$ considering logistic model $logit (p)=\beta_0 + ...
0
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1answer
13 views

Predictive model for meeting SLA

I have a big data environment in which tickets are solved by thousands of associates, across departments. There are multiple steps to solve the tickets and one ticket can go to multiple associates. ...
1
vote
1answer
84 views

Fuzzy RDD issue

I am fairly new to econometrics and maybe this is a very basic question to some. I am running a Fuzzy Regression Discontinuity (RD) design in Stata and I am having doubts about whether I am ...
0
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0answers
3 views

Multiple binary dependent variables

I want to model multiple binary outcomes with some predictors. Does MANOVA can handle this or is there any other techniques I can use? Thanks !!!
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0answers
3 views

have two ID with four dimensions and a mediator with two factors and a DV with four dimensions. [on hold]

want to calculate the direct and indirect effects between them. and what kind of techniques should used to analyze data from questionnaire. thanks
2
votes
0answers
41 views

Relationship between water quality at different sites and characteristics of study areas

I'm investigating the relationship between the mean values of water quality parameters and the characteristics (e.g. soil types (%), landuses (%), rainfall (mm), rock types (%)) of the study area ...
2
votes
2answers
245 views

Was this the appropriate regression model?

I was recently proof-reading a friend's thesis (for their writing, not stats usage) when I came across a usage of a regression model which I would regard as incorrect. However, I'm pretty new to the ...
0
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0answers
21 views

Should a BoxCox transformation to normalize the skewness of data be applied to all the predictors?

If there are few predictors that are highly skewed among a larger set of predictors in case of a linear regression problem, should a BoxCox transformation be applied to only these few predictors or ...
0
votes
0answers
52 views

Combining micro data for an econometrics paper

I am researching data for an econometrics research paper that I am doing but I am completely stuck. I am not looking for help doing the actual research, just guidance if my statistical method will be ...
1
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0answers
51 views

Multinomial logistic regression does not match actual data

I was wondering if someone with experience running multinomial logistic regression could look at my data file and results, and explain why the results turned out the way it did. The background: I've ...
1
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0answers
33 views

In a longitudinal analysis, is it valid to adjust for a covariate as change-score and also include the baseline covariate value?

We have a situation where we want to test the association between X and Y, but the change in X from baseline is more interpretable. There are several possibilities I see for setting up the model. But ...
0
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0answers
4 views

Function approximation, inverting and finding input values subsets based on output value

Suppose I have a set of input/output values for some unknown and complex function which I want to approximate using some machine learning algorithm. The input variables are integers or reals. The ...
0
votes
0answers
20 views

Given a covariance matrix from a Linear regression, how do I calculate the standard error of the coefficients?

I have an OLS with autocorrelation in the residuals. I'm using python statsmodels, and found that there is the sandwich_covariance matrix, which can cal Reference to Newey-West covariance matrix: ...
0
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0answers
37 views

R Logistic regression model - Error

I'm trying to run following command in R, but I'm getting an error ! any one could help and explain a reason for that ? ...
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0answers
78 views

“Do Teachers Matter?” By Slater, Davies and Burgess [on hold]

Has anyone of you read this paper "Do Teachers Matter? Measuring the Variation in Teacher Effectiveness in England" by Slater Davies and Burgess(2011)? I have a couple of doubts w.r.t. to this paper: ...
0
votes
1answer
48 views

Non-linear Model vs Linear Model for a dataset

I have a time series dataset for a city. The dataset contains rainfall amount and the number of repairman requests to a company. The company has 20 shops in different blocks of city and the rainfall ...
0
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0answers
19 views

Singularities in Multivariable Regression in R [closed]

I am running a regression in R on a dataset with 3 dummy variables (FEMALE, NONWHITE, and UNION) and 3 regular variables(AGE, EDUC(years of education), EXPER(years of work experience)). It is a CPS ...
3
votes
0answers
33 views

Will something terrible happen if my data points aren't independent?

Suppose I run a bunch of experiments, and get a bunch of datapoints, but several of the datapoints were derived from the same experiment. (In the extreme case, I just repeat the same datapoint 10 ...
0
votes
0answers
18 views

A reduced regression in SAS [closed]

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 ...
0
votes
0answers
24 views

Fitting a predictive model when I only care about the top values

I want to build a predictive model that given a certain set of features, predicts a value ( As in regular linear regression models). But as opposed to regular least squares, I actually don't care ...
1
vote
1answer
52 views

How to check linearity in binary logistic regression with many covariates having 0 as a value

I'm trying to check linearity in my binary logistic regression. According to my handbook (Discovering Statistics Using SPSS, by Andy Fields: ch.19.8.1) this should be done by adding var*log(var) to ...
0
votes
1answer
38 views

Can we use cluster analysis in multiple regression

I am quite new to Data Analytics. I was just wondering whether we can use cluster analysis in Multiple Regression. Let me give you a scenario so that it becomes easier to visualize. I have a dataset ...
1
vote
1answer
24 views

Prove that System FGLS is Consistent

In the Systems of Equations framework, such as Seemingly Unrelated Regression (SUR), suppose we have $g=1,\ldots,G$ equations. Let $\mathbf{X}_i$ be a $G \times K$ matrix, $\mathbf{y}_i$ be $G \times ...
1
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0answers
29 views

Power calculation for a coefficient in linear regression

Consider a simple linear regression of the form: $$ Y \sim \beta_0 + \beta_1 X + \beta_2 Z + \epsilon$$ I have questions regarding calculation of power for $\beta_1$. To calculate power, I approached ...
1
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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 ...
0
votes
0answers
44 views

Importance of independent variables; continious vs categorical

I have many independent variables which are affecting the outcome of a dependent variable (dependent variable is "return_impression" in figure below). When I measure the importance of these ...
1
vote
1answer
44 views

Linear model decomposition

Is is possible to decompose fitted linear model? What I mean by that: I have parameters of fitted linear model as following: y=2.3a-1.23b+1.65c+1.76d Now I have ...