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

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Utilizing A Correlation Matrix Derived from a Sparse Matrix

I have large correlation matrix in Excel that I'd like to use to inform my choice of explanatory variables in a multiple linear regression model. One problem is that the initial data was very sparse, ...
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1answer
33 views

Should a Poisson regression be carried out with only 3 data points?

I'm trying to test the relationship between the number of adults counted and the percentage heather cover over 3 areas. The data looks like this: ...
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10 views

How to compare the nested models which each of them comes from diffrent dataset?

I have four nested models.Every of them learned from different data sets. now I want to compare these models together.normally people try to compute the F-satistics. But for my case, it's bit harder, ...
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24 views

Significance of varibles after stepwise regression

I did stepwise regression with my multiple regression model and using AIC as a measure of fit with the step function in R. Afterwards some variables that the ...
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17 views

T-Tests and Regressions

my supervisor has asked me a few questions that I'm not entirely sure how to answer. For a quick summary, my study includes a small sample of 16. To describe the sample, I compared the scores of the ...
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9 views

predictive validity of personality traits in job performance of employees [on hold]

I am doing Phd research on "Role of personality traits in predicting the job performance of employees". I have a sample of 500 managers and used the big five personality theory to measure traits of ...
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2answers
36 views

Capturing Seasonality in Multiple Regression for daily data

I have a daily sales data for a product which is highly seasonal. I want to capture the seasonality in the regression model. How I can do it? I have read that if you have quarterly or monthly data, in ...
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1answer
17 views

Dealing with Categorical variables in Multiple Regression

I have a data having 2 continuous and 4 categorical variables. Each categorical variable has 3 levels. I want to know how to include the variables in the model. I am using SPSS Variables: Sales - ...
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5 views

Class complexity vs mean absolute error vs mean squared error when doing regression on continuous vars

I am trying to do regression on the weight of fish caught given a number of continuous parameters, using Weka I'm using 1-12 parameters and a sample size of 5000-15000 A typical output is ...
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8 views

Significant variables, but no improvement on predictive ability of model

When running binary logistic regression in SPSS, I obtain first a measure of the predictive ability of a model without independent variables (base model). This is then compared with that of the model ...
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17 views

How to test whether a distribution follows a power law?

I have the data of how many users post how many questions. For example, [UserCount, QuestionCount] [2, 100] [9, 10] [3, 80] ... ... it means each of the 2 users posts 100 ...
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7 views

What is a “concordance score” for regression coefficients?

I came across this "concordance score" in a set of slides called Penalized regression methods for ranking variables by effect size, with applications to genetic mapping studies, by Ji Zhu: $$ ...
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9 views

Calculate coefficients in a ordinal logistic regression with R

Following the question about manually fitting logistic regression, can someone provide the same 'manual' way to fit a ordinal logistic regression with ordered categorical response?
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28 views

Simplifying numerous dummy variables

I'm looking into a regression analysis to compare the time it takes to award public contracts across different countries but holding some other variables constant is proving challenging. The set of ...
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22 views

How to represent bayesian loss function in binary classification

I am studying classification using linear regression . Now, I want to map it in Bayesian regression. Let talk about binary classification using linear regression again. Assume that I have a set ...
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20 views

binary logistic regression in spss version 22

I'm trying to run a Binary Logistic Regression. I have multiple IVs and 1 Binary DV. Can anyone show me how to do this with SPSS v.22? (or which one to select from this list) thank you
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15 views

Number of significant linear predictors if predictors are not independent?

I would like to determine which of a set of candidate predictors $\{x_1, x_2,\ldots, x_n\}$ are significantly relevant to the linear prediction of $y$. Typically, one can compare a full model ...
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24 views

Robust regression in R with robust::lmRob

I am using the lmRob function in R to do my robust regression. In the R documentation of lmRob found here you can set the ...
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20 views

Using the coefficients of regression for giving weight to the data

I want to perform clustering on my data set. I used spectral clustering and obtained an acceptable result. In an effort to (maybe) improve the result, I thought of applying a linear regression on my ...
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1answer
43 views

How to solve for the parameters in a logistic function? [duplicate]

I want to find the parameters of a logistic function. I read the guide here. It has a very clear explanation, but it did not have the final solution that I need. Now, we will consider a basis ...
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28 views

Defining a simple linear regression of reaction times against stimulus number

I have reaction times for each of nine stimuli (the stimuli being the numbers 1 to 9), all 9 variables being arranged as columns, and with subjects across rows. I would like to regress those scores ...
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1answer
55 views

Great model prediction, but no significant variables

I am performing a binary logistic regression. I have developed a simple model which I am testing using the SPSS application. This first determines the predictive ability of a baseline model without ...
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9 views

Ordinal Logistic Model

I am new in research and have just started. My anticipated study is on ''determinants of community participation in planning for HIV and AIDS non medical interventions. Now the question is if the ...
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2answers
93 views

How to cope with missing data in logistic regression?

I'm investigating optimal bidding in auctions, and am using logistic regression to predict the probability of winning an auction given a set of explanatory variables (e.g. the price I bid, number of ...
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Conduct a hypothesis test of each regression coefficient [on hold]

A regional planner is studying the demographics in a region of a particular state. She has gathered the following data on nine counties. Country Median Income Median Age Coastal A $48,725 ...
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17 views

R: Fitting a model with periodic, nonlinear and categorical components

Can anyone give me some advice on how to fit a model with linear (some categorical), non-linear and time series components in R? I don't want to use a non-parametric model like a Loess smooth or ...
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3answers
52 views

Similarities and differences between correlation and regression

If I want to investigate how two continuous variables are linked, what is the difference between calculating the correlation coefficient (Pearson's r) versus calculating the (simple linear) regression ...
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5 views

How to interpret factor coefficients regarding unobserved values?

I am presented with a linear regression result that yields the following coefficients: ...
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15 views

values for categories [on hold]

Appreciate if you can help me with the following. I have created categories High, medium and low and I need to transform them in ordinal numbers for further calculation. What is the best approach to ...
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2answers
88 views

Hat matrix,$H=X(X^{\prime}X )^{-1}X^{\prime}$

What is the importance of hat matrix, $H=X(X^{\prime}X )^{-1}X^{\prime}$ in regression analysis? Is it only for easier calculation ?
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1answer
28 views

Getting all zero correlations,$\rho_{ij}=\frac{\mathbb cov(e_i,e_j)}{(V(e_i)V(e_j))^{1/2}}$

Consider the general regression model $$Y=X\beta+\epsilon$$ where, $Y$ is an $(n\times 1)$ vector of observations, $X$ is an $(n\times p)$ matrix of known form, $\beta$ is a $(p\times 1)$ vector ...
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17 views

Preconditioning the intercept for Logistic Regression

I am working on implementing a Logistic Regression model, using the newton-cg and lbfgs optimsers provided by scipy as the backend. I find the problems in which I fit the intercept, to be 50% slower ...
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21 views

Which statistics to use calculating prediction interval of dummy linear regression?

I have performed a linear regression and found a model of the form: $$ \hat{Y} = \alpha + \beta_1 x+ \delta_{high} + \delta_{low} + \epsilon\\ $$ Where: $\beta_1$ is a continuously distributed ...
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11 views

How to use regression analysis to set an optimal price

I am working on a side project with very small dataset where i am trying to figure out the optimal price i should set for a transaction fee (something like payPal). Currently i am using an arbitrary ...
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23 views

Finding rules in a dataframe in R [on hold]

If I have a file like this start end [1,] 1 1 [2,] 2 2 [3,] 4 4 [4,] 5 5 [5,] 7 7 [6,] 8 8 Is it possible to make rules ...
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1answer
24 views

Why does SAS Enterprise Miner keep all dummy variables for a coded categorical variable in stepwise logistic regression?

SAS Enterprise Miner nicely creates coded dummy variables for any categorical variables used in a logistic regression model. When it performs a variable selection using stepwise sequential selection ...
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12 views

Cross-sectional SUR in R

Is there a package in R that can estimate panel data with cross-sectional seemingly unrelated regression generalized least squares weights (like in EViews)?
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1answer
63 views
+200

ARIMA Intervention Transfer Function - How to Visualize the Effect

I have a monthly time series with an intervention and I would like to quantify the effect of this intervention on the outcome. I realize the series is rather short and the effect is not yet concluded. ...
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1answer
21 views

Reducing the number of interaction terms in a diff-in-diff model?

Is there a way to reduce the number of interaction terms in a diff-in-diff model to make the results easier to interpret/present? Background: I'm trying to run the following diff-in-diff regression: ...
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1answer
65 views

demonstration of benefits of ridge regression over ordinary regression

I can understand ridge regression is better than ordinary regression in case of multiple-collinarity. ...
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28 views

R GLM verifying performance statistics for validation

I do not want to say my AUC is 0.77 and find out I am overlooking a lot. Below is my code and a two question at the bottom: ...
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38 views

How can i show mathematically Partial Least Square Regression is better than other Ordinary Least Square Regression?

I want to develop techniques for attribute selection (important independent variable X) using Partial least square 2 regression(PLS2R) for a large data sets .Initially i tried using multivariate ...
2
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1answer
18 views

Can I difference after fitting a time series regression model?

Suppose that I have a time series that exhibits a notable trend, and I want to test a hypothesis that a second variable is related to that trend. I fit a linear regression model with that second ...
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14 views

Weighing a variable based on distance to a known date

In a bankruptcy model, you want to assign a higher weight to a variable as a big event date approaches (such as a company's quarterly earnings announcement date) and you reverse this weighing as you ...
1
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1answer
18 views

Repeated measure nested within individuals?

All, (I'm a beginner so my question could be really dumb...) So, I have a set of data that contains 30 schools' variable A and variable B. These two variables were measured repeatedly each year for ...
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19 views
+50

Predicted probabilities from simulated betas and hypothetical data after conditional logit?

I'm working with conditional a conditional logit model to avoid bias that comes with FE logit models, when it comes to generating some hypothetical substantive effects, however, I run into trouble. ...
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13 views

which regression model: nested, censored data

I have the following data structures and would like to know your opinion which regression models are most suitable (and available in R) model 1: - 20,000 cases - nested in 500 spatial units (only ...
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0answers
20 views

dichotomizing a predictor variable [duplicate]

Does dichotomizing a predictor variable always reduce the power in a linear regression model? We have a normal distribution for a predictor and then have sampled just from the high and low parts of ...
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2answers
55 views

Linear and semi-log regression model

Is this equation: $$\log{(y)} = a + bx$$ semi-log or log-linear mode (or it is the same thing)? I have two models: linear (1) and semi-log (2). The values of $R^{2}$, adjusted $R^{2}$, and ...
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4 views

Repeated multiple regression for LASSO significance testing

I'm currently working on a statistical modelling problem in biology. We have cellular measurements of proteins in every cell in a tissue, and I'm using regression analysis to see if a given protein is ...