Questions tagged [log-linear]

The log-linear model is a form of Poisson regression that allows for the analysis of multi-way contingency tables.

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Mean Log10-Linear regression

In field experiment I have gathered data for X and Y with the aim to fit a regression and use X to predict Y in the future. Based on physics, I know the relationship should be of the form $y = 10^{a \...
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38 views

How do you change log-linear transformed prediction interval values for a regression back to original scale in r?

I have a simple regression model where I needed to log-transform the dependent variable because the model residuals were non-normal. Now my model is ok in that respect. So, I ran the model. But, ...
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Differing AAPC and Confidence Intervals Using the Joinpoint Regression Trend Analysis Software vs R

Let's say I have a data-set with trend data looking at an adjusted rate by year from 1980-2000, with a standard error associated with it: ...
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Does benfords law imply a log scale for the distribution?

We see Benfords Law in a lot of real world data sets, with the general derivation that if things are distributed symmetrically on a log scale, then the law holds. However, it's not obvious to me: Why ...
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Mixed-effects log-linear regression for counts -

I've read other answers but couldn't find exactly what I was looking. I have generated the following contingency table from my data: ...
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Using Ordinal (Star Rating) variables to predict outcomes in Log lin regressions + Taking Median significant coefficients of multiple regressions

Framing the regression I am attempting to analyze the effects of several variables on clicks for Google My Business listings. Currently I'm using a Log-Lin regression model to predict the % increase ...
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235 views

Why AIC for log-linear model in glm returns Inf?

I am trying to calculate the AIC for log-linear model in R, but i get Inf as a result. The model aim is to predict sales in euros based on some variables. As far as ...
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Heteroskedasticity leads to inconsistent estimate in log-linear model

My question concerns the following paper. Silva, J. M., & Tenreyro, S. (2006). The Log of Gravity. Review of Economics and Statistics, 88(4), 641-658. doi:10.1162/rest.88.4.641 To summarize, ...
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52 views

Can't find loglinear model's corresponding logistic regression model

I have the loglinear model with parameters x, y, z, v, xy, xv, and z*v. As far as i understand there should exist a logistic regression model that essentially is equivalent to this, using v as ...
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34 views

Can $G^2$ statistic in log-linear model for contingency tables be negative?

Can $G^2$ statistic of log-linear (unsaturated) model in contingency tables be negative? Since saturated model with perfect fit has $G^2=0$ I don't think the unsaturated models can get negative $G^2$. ...
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How do you interpret residuals of log linear models with categorical variables?

I have researched to find an answer for this question on the internet but have not found many examples / answers. One thing I have found is to calculate $\frac{O-E}{E^{0.5}}$ which has a normal ...
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How many parameters would the saturated model have if there were no constraints?

In a saturated log-linear model for three variables, the equation is $\lambda+\lambda^A+\lambda^B+\lambda^C+\lambda^{AB}+\lambda^{BC}+\lambda^{AC}+\lambda^{ABC}$ I understand that we have to impose ...
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55 views

log-linear modelling: transforming y variable

I am conducting a study on graphical log-linear modelling and my aim is to fit a log-linear model to data. I am using R studio to carry out the analysis and I am using the glm function. When first ...
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How Can I Interpretation in loglinear regressions with coefficients greater than 1

I run a loglinear regression and got dummy variable coefficient for education level bigger than one. It's also significant and my depend variable's log wage. How would I go about to interpret the 2.21?...
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Correlation of categorical data to binomial response in R

I'm looking to analyze the correlation between a categorical input variable and a binomial response variable, but I'm not sure how to organize my data or if I'm planning the right analysis. Here's my ...
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54 views

Mean of predicted values in a log-linear model

I run a log linear model $$\log(Y)=\alpha + \beta X + \epsilon$$ and wonder how to calculate the mean of predicted values, in the same dimension as the initial (untransformed) variable Y. I would ...
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Log-linear fit and parameters in case of perfectly correlated variables

Here is an example case. Take the following ´data´: ...
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1answer
85 views

Check if dropout rates are independent for an interaction of two independent variables (one with a large amount of levels)

I am trying to analyse dropout rates in an experiment, but there are multiple issues which collide, and I don't know how to deal with them as a whole. First, find a list of those issues. Below, see a ...
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100 views

Statsmodels - 'corrected predictors' on log-linear models?

I'm currently working through an econometrics book , and in the section about log linear models it is stated that predictions made with ...
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73 views

Log-linear model for contingency table with no fixed count

I have table of counts of born children with four two-level factor variables (mother smoker/nonsmoker, child born dead/alive, ..). I would like to use log-linear model to understand interactions of ...
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75 views

Help needed to Interpret ln(y) = a +b (Standardized X)

I am analysing server data and I have a scenario where I need to get the % by which Y is changed because of a unit change in X: EDIT: I am doing a Linear Regression in Python (and its other forms ...
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357 views

Appropriate way to visualize significance in 2x3 contingency table using mosaic plot

I've checked multiple threads about handling or visualizing contingency tables, but can't find one that can help my current question. I have a 2x3 contingency table: "group" variable has 3 levels not ...
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Interpreting log-linear model for contingency table in R

I'm looking at sample data and trying to determine whether there is any association between the height of the husband and that of the wife below. I don't fully understand what the symbolic ...
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566 views

Log-linear difference-in-differences

I am estimating several linear models using a difference-in-differences (DiD) framework. The model interacts a treatment indicator (i.e., 1 for the treatment group, 0 for the control group) and a "...
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1answer
125 views

Bivariate analysis as a basis for a subsequent analysis?

I have run across many research articles which used bivariate analysis, whose results become the basis for a subsequent analysis. For example, a Chi-squared test was used as a preliminary analysis to ...
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Log-Linear Output Help

I ran a loglinear model with 3 variables. Internet Use (Y/N), Nervous Breakdown(Y/N), and Happiness (3 levels). I understand by two way interactions are significant, but I am getting lost trying to ...
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logliner analysis on SPSS with more than 10 variables

I want to run logliner analysis on SPSS Statistics 25 but I have more than 10 variables.= 1 outcome variable and 11 predictors/factors. The big number of factor variables can be explained by the fact ...
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109 views

Log-linear regression: interpretation of RSE

AIM: To really, really understand what the model outputs mean in a log-linear regression, specifically, how to interpret the residual standard error (RSE). I have read this post but it does not ...
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2k views

Confidence interval of a log-linear regression

AIM: Make a confidence interval statement on a log-linear regression I have read posts like: Interpreting Standard Deviation of Natural Log Transformed Data Lognormal Regression? But they do not ...
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INTERPRET A REGRESSION MODEL WHEN OUTCOME VARIABLE IS LOG TRANSFORMED [duplicate]

I have used a linear model between a log-transformed outcome variable and a group of predictor variables. In this model, the dependent variable is in its log-transformed state, and the independent ...
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111 views

Poisson log linear Regression: using either R or python

I was hoping someone can help me with this problem. I posted a similar question earlier but it's not the same. I have the following: A 2x2 matrix of structural connectivity values between brain ...
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2answers
519 views

Interpretation of β in case of log-lin model for relationship between X and Y

In many papers, the dependent variable is transformed by taking natural log. For instance, consider the following model: $$\newcommand{\Cov}{{\rm Cov}} \ln(\text{Y}) = \alpha + \beta\, X_1 + \epsilon ...
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Logistic regression and log-inear [closed]

I do not know why log-linear is non-sensitive margins and logistic regression is sensitive margins. Both are using odds ratios Can anyone give some explanation.
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Predicting probabilities after log-linear regression

I would like to estimate a log-linear regression and examine the results with Stata's marginsplot command. I have transformed my dependent variable into natural logarithm (to make a highly skewed ...
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1k views

Check log-linearity of a continuous variable to predict survival

I have the following survival data: cases with a continuous variable risk_factor wich higher values having a higher HR (1.026, CI: [1.017-1.034], p = 2.03e-09) for ...
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What is the appropriate analysis for this type of repeated measures multi-binary data?

There is a popular theory within psychology that certain emotions will trigger "prototypical" facial expressions defined by the simultaneous contraction of specific facial muscles. For example, if a ...
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904 views

Log-linear regression preferred over logistic regression for categorical vars?

I read here that, when all variables are categorical, log-linear is preferred over logistic regression "because log-linear is merely an extension of the chi-square test." I don't have a stats ...
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Conceptual question about log-linear analysis

I have measured the binary occurrence of three types of events on multiple days. Theory suggests that these events are not independent and should occur on the same days more than would be expected ...
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1k views

How do I interpret the coefficients of a log-linear regression with quadratic terms?

I have a regression equation of this kind: $$\log {y} = a + bx + cx^2 + \epsilon$$ where $a$ is the intercept, $b$ and $c$ are the coefficients of $x$ and $x^2,$ and $\epsilon$ is the error. How do ...
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How can I interpret intercept when my dependent variable is in log form?

My model consists of both log independent and dependent variables, and percentage share, as well as number of people and etc. My dependent variable is log(GPD per capita in USD), my statistic package ...
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1answer
64 views

Newton-Raphson Error

According to Agresti(2013) pg 364-365, iterative methods such as Newton-Raphson methods, $ \begin{aligned} \beta^\text{new} &= \beta^\text{old} + (X^{T}WX)^{-1}X^{T}(V) \end{aligned} $ help to ...
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Log-normal vs. log-linear vs. logging the response variable

I've been reading a lot of Wikipedia pages and StackExchange/CrossValidated posts, and I have come to a point where I realize I do not understand some of the terminology I have been using. What's ...
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546 views

How to add a covariate to a contingency analysis?

Scenario Consider you ask kids whether or not they like guns (yes/no answer). You also ask them whether they watched an action movie in the past two days. Then, you are willing to see if there is ...
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491 views

How are graphical models “a subset of log-linear models”?

Caveat lector: I am not sure what is meant by a "log-linear model". The Wikipedia page makes it seem as if log-linear model is an alternative term for exponential family. This description of a book ...
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1answer
130 views

Log-linear model vs Multinomial-Dirichlet model for contingency table

Given a 1x3 contingency table of the form $$[y_1,y_2,y_3]$$ where each $y_i$ represents a count on some random variable $$X\sim Multinomial(n, \pi_1,\pi_2,\pi_3)$$ We can estimate the vector of ...
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2answers
2k views

Poisson regression vs log-linear model

I'm confused about the difference between log-linear model and poisson regression and I am not sure which one to use to answer my research question. In the experiment, participants were grouped into ...
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280 views

What does it mean if the residuals for a log-linear model are all zero?

Probably a very basic question, but I have a contingency table formed of 3 categorical variables (one with 3 levels, the rest with 2) and have been asked to try to test the association between them ...
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263 views

Interpretation of loglinear regression [closed]

Let's assume that gender is the only predictor in binary loglinear regression, in which we are predicting odds of getting paranoid schizophrenia (females are marked as 1 and males as 2). If loglinear ...
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138 views

How is a covariate added to a log-linear model?

There are a number of good Q/As about log-linear models (i.e., here). The data I am analyzing is off shifts between categories, 0, ...