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

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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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9 views

Could Use Assistance On A Work Project

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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10 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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15 views

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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4 views

How to model this continuous-poisson data across samples?

I have conducted a drug test where on the x-axis I measure the amount of concentration for the drug. This is obviously a non-negative continuous variable. On the y-axis, I measure the proportion of ...
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11 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
20 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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3answers
208 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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5 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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1answer
28 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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20 views

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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6 views

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
48 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
39 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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9 views

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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8 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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64 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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0answers
74 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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25 views

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

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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13 views

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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1answer
48 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 ...
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3answers
53 views

Ranking of categorical variables in logistic regression

I am doing some research using logistic regression. 10 variables influence the dependent variable. One of the aforementioned is categorical (e.g., express delivery, standard delivery, etc.). Now I ...
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1answer
23 views

Simpson's Paradox & Random Effects

Simpson's effect is key to understanding potential pitfalls in medical research, particularly in the area of meta-analysis, where multiple studies with dissimilar methodologies are brought together to ...
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2answers
24 views

Need help double checking results of Binary Logistic Regression in SPSS

I'm working on some of my analysis section for my Master's Thesis in MPA, and while I have consulted my professors, I'd just like to double check with some external eyes (As obviously they are on my ...
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1answer
42 views

logistic regression with an imbalanced data set, picking threshold cut point

This question relates to whether it is a good starting point for a cut point in binary classification with logistic regression to the use the mean of the binary response variable as the initial cut ...
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2answers
33 views

segmentation of univariate irregular time series

this is my first post. I have an irregular time series that exhibits large shifts in both mean and in the direction of the trend. It looks something like this (though this is far cleaner than ...
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15 views

How to analyse the influence of 100 categorical or continuous predictors on one continuous response?

I am analysing a genetic dataset that consists of 288 individuals, 100 genetic markers as predictors and one continuos variable (day of death) as outcome. Each predictor has three categories or ...
2
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1answer
40 views

Consequences of violating proportional hazards assumption in Cox model

What are the consequences of violating the Proportional Hazards assumption in a Cox Model? I've got a Model where two factors are highly significative, but all the estimated betas associated to the ...
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1answer
49 views

Linear Regression Prediction Interval for precise y values

When calculating the prediction intervals for a regression function, can the y values be precise values "without errors"? As far as I know, in regression function calculation only the x values are ...
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1answer
25 views

Combining multiple OLS Regressions

I have a single output $y$, and multiple inputs $x_1, x_2,\dots,x_n$. I am running online(streaming) regression, which would be complicated with many inputs. So, to go around it, I want to have $n$ ...
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38 views

What exactly is the critique in this regression?

Warning: I might be forgetting basic statistics here. Please edit title if it can be improved. This paper, seemingly summarized in the fancy ZUI slideshow here, points out a possible "critique" in ...
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29 views

Is this analysis sufficient, have I overlooked important statistical tools/terms [on hold]

I'm doing a master thesis project, looking for patterns between two datasets. I have not had any statistical courses or similar. So I'm in doubt if I'm on the right track. Any comments or tips/tricks ...
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Using correlation to eliminate predictors?

I have 1 dependent variable and 33 independent variables (continuous, categorical & dichotomous). Correlation analyses (2-tailed) show that the DV is only correlated to 7 of the IVs although most ...
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Why is multicollinearity not checked in modern statistics/machine learning

In traditional statistics, while building a model, we check for multicollinearity using methods such as estimates of the variable inflation factor (VIF). But in machine learning, we instead use ...
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2answers
82 views

Log vs square root link for Poisson data in R

I am currently working to model deaths from AIDS over time using a GLM in R. I know that there are two possible options for the link function for Poisson data, log and square root. I know that square ...
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Difference-in-Difference with Heterogeneous Effects

Suppose that I have the following two group two time Difference-in-Difference model: $Y_{it}=\alpha_{0}+\alpha_{1}*d_{t} + ...
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Correlation regression

I have a multiple regression model with 4 independent variables and 5 control variables. y=x1+X2+X3+X4+x5+X6+X7+X8+x9. and i have 4 null hypothesis to test the relationship between the independent ...
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19 views

How to correct the means of a variable in 4 groups matlab

I compute the mean of the variable Y in 4 groups (A B C D) that differ for age, gender and body mass index (BMI). ...
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0answers
18 views

How to obtain coefficients for Generalized Poisson regression model in stata? [on hold]

I am interested in applying Generalized Poisson regression model for my count data as the my dependent variable variance is less than the mean. I used "gpoisson" command in stata. However, I am not ...
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15 views

Proportion z test for predictive model

I have deployed two models, the baseline one which only includes historical data of a stock market index and the twitter model which includes both historical data of the index as well as significant ...
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1answer
26 views

Can a variable become statistically significant after the addition of another variable? [duplicate]

I am doing forward stepwise logistic regression. I have heard that its common for a previously statistically significant variable to become not statistically significant when one or more variables are ...
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1answer
33 views

Regression with latent variable response

I have a dataset with the following structure: $(x_1,x_2,x_3,...,x_n, y)$ where $x_k$ are some categorical predictors and $y$ the numerical (integer) response. Assuming that $x_1 \in \{a,b,c\}$, ...
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46 views

Survival Cheat Sheet ANOVA Alphabet Soup & Regression Equivalents

Can I get help completing this tentative (in progress) attempt at getting my bearings on ANOVA's and REGRESSION equivalents? I have been trying to reconcile the concepts, nomenclature and syntax of ...
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15 views

Diagnostic regression for checking the validity of clustering results

I have done an unsupervised non-parametric clustering on sample data gathered by a questionnaire for my thesis (k-means algorithm). A referee asked me to do a diagnostic regression for checking the ...