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

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Gradient Scores from Binary Logistic Regression

My research concerns the language of Alzheimer's patients. As the disease progresses, their language becomes more concrete and less abstract - they seem to 'lose' their abstract vocabulary more ...
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7 views

Applying parametric tests on non-parametric data

I'm doing a research and I have some concerns, and I'd appreciate your kind assistance on them. Basically, I'm designing an instrument to measure something (a single dependent variable), and I'm ...
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10 views

Merging observations in Gaussian Process

I am using Gaussian process (GP) for regression. In my problem it is quite common for two or more data points $\vec{x}^{(1)},\vec{x}^{(2)},\ldots$ to be close to each other, relatively to the length ...
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16 views

how should I do regression analysis where response is number in each category

I try to find genes that related to output which is numbers in three category. The simplified analogy is: first we take an zygote and measure the expression of a gene, and clone this zygote to many ...
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11 views

R survreg returns reciprocal of incidence rate ratios?

I'm working through some poisson regression for survival data using R. As I understand it, the exponentiated output from survreg with dist = "exponential" should give the incident rate ratios. I ...
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20 views

Interpretation of linear regression where the outcome can only possibly cause the value of predictors and not viceversa

We want the verify the association between artificial pregnancy (artificial insemination) versus natural pregnancy and a series of pregnancy conditions (hypertensions, diabetes, etc). We first ...
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12 views

Interpreting interaction term via margins command? [on hold]

I am using Stata. I regressed test score on a wealth dummy (high/low) and a maternal education dummy (high/low) and some control variables, among them age (3,4,5 and 6 years), in a linear regression. ...
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1answer
15 views

Advice on a model or approach to layered dataset

I am attempting to develop a model to estimate the number of people in a space based on the Wi-Fi Traffic. At present, I have a dataset (in xml) which is structured like the following: ...
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7 views

How to use co linear variables in developing a model

I am trying to develop a model to predict a price which depends on market indexes, Market indexes are correlated (they rise and fall together). Price also changes in same direction with indexes. I ...
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6 views

large difference between pearson and deviance residuals

pearson deviance 7.46917 2.8423 6.85298 2.78224 I am fitting logistic regression model in SAS. What should be reason of large difference between pearson and deviance residual as mentioned above ?
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26 views

Can I use Cox Regression here?

I have a data-set where I want to do a regression of survival probability given amount of drug injected into a subject. The more drug injected, the less likely the subject will survive after say, 3 ...
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28 views

How should I check the assumption of linearity to the logit for the continuous independent variables in logistic regression analysis?

I am confused with the assumption of linearity to the logit for continuous predictor variables in logistic regression analysis. Do we need to check for the linear relationship while screening for ...
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32 views

Why would I need both a validation set & a test set if I'm not selecting a model?

I have a dataset with two features and one outcome. I was asked to separate the data into three parts such that 70% of the data is a training set, 20% is for validation and 10% for testing. The model ...
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19 views

Interpreting circular-linear regression coefficient

I'm trying to use the circular package in R to perform regression of a circular response variable and linear predictor, and I do not understand the coefficient ...
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83 views

Model selection, issues of judgement

I have a general question on model selection strategies in regression models. In my research, the main goal is rarely prediction but almost always estimation of effects of certain variables. I have ...
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1answer
28 views

Difference between modelling and testing association

I have data set with binary outcome, with 5 continuous covariates and 4 discrete covariates. I am little confused as to how I test for association, for the discrete covariates, I used a chi sq test, ...
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16 views

Segmented Regression With Control Group Implementation and Interpretation

I have been reading the following paper on segmented regression for interrupted time series - Wagner 2002 and wanted to learn a proper analysis of such data where there is a control group. The paper ...
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19 views

Constraining coefficients in linear regression

I am trying to estimate a model of how rail freight shipping rates are effected by a number of different variables, including the price of fuel. There is such little variation in the price data that ...
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1answer
32 views

Forecasting - Population Death Rates

Wondering if you can help me out with this problem: I have 2 closed populations of products (call it Product X, and Product Y). Population Size of each product 10 million each (Product X = 10 ...
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19 views

Partial Least Squares regression

Assume we have a simple linear regression model expressed as $Y= X \beta + e$, where $Y$ is a vector of size $n \times 1$, $X$ is a matrix of size $ n \times p$, $\beta$ is the regression coefficients ...
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24 views

Three Different Regression Results… Why is one so weak compared to the other two?

I have a data set I'm working with, it's roughly 450K rows of data. I'm breaking the data out from a certain column, and that column has three results. After that, I ran a regression analysis for each ...
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1answer
15 views

Testing a single time-series for changing variance structure (Heteroscedasticity and Volatility Clustering)

I would like to assess a single time-series for a changing variance structure that might be leading to spurious variance estimates when that time-series is used in regression. In my head two terms ...
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4 views

Changing polynomial degrees leads to different coefficients in Fuzzy RDD

I am running a Fuzzy RDD and I am getting some unusual results, the coefficient of interest changes sign and significance with different polynomial specifications. When using a linear polynomial ...
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14 views

Interpretation of odds ratio in logistic regression

In the study of birth weight (low or normal) of a child, the "birth term" of the child has been considered as a risk factor. The birth term has two categories: premature and full-mature.The following ...
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16 views

association between discrete variables and continuous variable

I am having little difficulty with understanding the difference between, testing association between two variables and modelling them. Say I have binary outcome x(sold, not sold), and i have all ...
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17 views

Could Use Assistance On A Work Project [on hold]

This might be a little unorthodox, but I could use some assistance on a work project. I work for a small company. We don't have any formal data sciences or analytics department. I was tasked with a ...
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13 views

Improving estimates of linear system regression when parameters are unevenly weighted

I have a system with a linear model $ax + by = c$. I can adjust $a,b$, measure $c$ (with some error in the measurement) and then use linear regression to estimate $x,y$. The problem I'm running into ...
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Regression analysis of a correlation coefficient

I have a time series of the 250 day historical correlation and I need to determine what causes this correlation to change as different explanatory variables change. Is there a way that I can regress ...
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12 views

Cross country OLS regression

Need help as this is my very first experience with panel data.I am studying impact of stock market on economic growth(GDP per capita). for that, panel data consisting of 60 countries from 2001-2011 ...
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1answer
25 views

Comparing Height of Web Page against Scroll %

I have a collection of 108 data points in the following format: page height | % of users who scrolled upto 25% of page | 50% | 75% | 100% (full page) I'm trying ...
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215 views

How do you call multiple linear regression when it has an interaction term?

I'm writing a report and need to be precise but concise in the abstract. Currently I called it 'multiplicative multiple linear regression'. But when I Googled it, not much came up. In the same vein, I ...
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6 views

Problems facing in fitting ordinal regression model on life satisfaction data

While running an ordinal regression analysis of life satisfaction data SPSS, I got the following warning: There are 148 (65.8%) cells (i.e., dependent variable levels by combinations of predictor ...
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6 views

Moderation Analysis: Correlation Coefficient or Fisher's r to z

I was wondering if anyone knows whether correlation coefficients or using the fisher's r to z transform may be more appropriate to enter as a predictor in a moderation analysis? Thank you for the ...
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29 views

Gaussian processes ordinal regression in R [on hold]

Is there any ordinal regression using gaussian processes implemented in R? I made a research in the Internet, but I didn't find anything.
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Allocation of design points in an experiment

I would like some hints with the following problem. Thanks for any help in advance. An experimenter wants to design an experiment for estimating the rate of change in a dependent variable Y as an ...
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Compare two simulations results of similar systems

I am simulating transcription regulation (a biological process) by four different mechanism using Ordinary Differential Equations. I am not sure about how to compare two different simulations (the ...
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31 views

Linear regression interpretation

Lets say I run a port. There's this ship coming with watermelons and melons. They have multiple containers, which I cannot open, with mixed watermelons and melons. From the source port, the ...
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2answers
56 views

Logistic regression is predicting all 1, and no 0

I am running an analysis on the probability of loan default using logistic regression and random forests. When I use logistic regression, the prediction is always all '1' (which means good loan). ...
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1answer
47 views

How to start with regression analysis? 10 variables; 1M samples

My statistics knowledge is limited, and it appears that I have a task which would benefit from regression analysis. Please direct me. I've around 10 variables (A, B, C, ...) which might be related to ...
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How quickly will gradient descent converge given only a single training example for a regression problem?

This scenario is mostly academic or of conceptual interest. It might not make much sense in real life. Consider the case when we are trying to learn a regression function via gradient descent. Say we ...
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11 views

Multiple Response Regression in Spark MLLib

I am trying to do a regression using RandomForests in Spark ML where I have several input variables and would like to predict several responses. Training data would look like X = ...
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22 views

What happens to the coefficients when we switch labels (0/1) - in practice? [migrated]

I am trying to see in practice what was explained here what happens to the coefficients once labels are switched but I am not getting what is expected. Here is my attempt: I am using the example of ...
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18 views

Regression plot and function for: heavy-tailed probability distribution

I've got data points from a simulation as coordinates in a text-files like so: ...
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14 views

Binary logistic regression - SPSS

I did some regression analysis in SPSS using two binary variables: Biomarker X (0= low levels; 1= high levels), where 0 was the reference category and Obesity (0=no; 1=yes) ''Biomarker X'' was taken ...
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67 views

Structuring Many-Factor Data for Linear Regression in R

I have a fairly large dataset of the following form, and I want to run a linear regression returning coefficients for each factor: ...
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80 views

Question about the answer to “Local polynomial regression: Why does the variance increase monotonically in the degree?”

I appreciated Marco's elegant answer explaining why the variance of a local polynomial regression increases monotonically in the degree. However, in the end of the proof, I find difficult to calculate ...
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27 views

How do we interpret the parameters of a nls regression model? [closed]

The data for these results are from two different seasons (A & B). Please explain with regards to the parameters (a,FRE & FGPP) in the model. FREE and FGPP are also response variables. NEE ...
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21 views

Comparing regression coefficients using F-test to assess for batch effects

Here's what I have: two datasets with ~27,000 variables (same variables for each dataset). I'm trying to test whether or not dataset1 and dataset2 display batch effects. Namely, I want to do PCA and ...
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Penalized methods comprehensive overview

For the last 10 years from 2004 we have seen a growth in the number of different regularization techniques that have been in use. First it was LASSO, then Adaptive-LASSO, Elastic Net, SCAD, MC+, just ...
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51 views

How we can compare two coefficients of one linear regression?

I have this regression model, $$\hat{Y}=\hat{a}X_1+\hat{b}X_2+\hat{c}$$ Both $X_1$ and $X_2$ are significant at 0.01 level. $X_1$ and $X_2$ have a same unit. Now I want to find a test that tells me ...