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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Suggestions for an independence test in a complex design

In an experiment I surveyed the effect of two treatments (pre & post) in different species. After every experimental run I tested whether the measured average effect was greater, smaller or not ...
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Why does log-linear analysis seem to ignore the Poisson regression equidispersion assumption?

As far as I understand it, log-linear analysis is based on the use of a Poisson regression. This is what I understood from various online resources, like this online tutorial or this text whose intro ...
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How do I choose which variable transformation (logY~logX/logY~X/etc)? [closed]

I'm doing a linear regression assignment using a variable transformation using R. and I have several questions. What is the criteria of choosing which type of variable transformation? We've learnt &...
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Visualizing relationships in log-link/exponential distribution models by placing the linear predictor on the Y axis?

I'm visualizing results from a negative binomial regression. I don't want to the graph of Y vs X to look exponential, I want it to look linear. In SPSS, the value provided for the linear predictor is ...
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How to correctly perform a goodness-of-fit test for a contingency table (two-way, three-way, or more), in situations other than independence testing?

Let's say I have the following table from a sample of 462 people: Gender Happy Meh Sad Men 70 32 120 Women 100 30 110 I don't want to test it against the hypothesis of independence, but against ...
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taking log of a variable with values of 0 [duplicate]

I have an outcome variable 'expenditure' which I believe may be non-linear in nature so I am running a log-linear regression after taking log of the variable. However, there are values under ...
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Intercept and dummy coefficient interpretation in an inverse hyperbolic sine transformed dependent variable in linear regression

I am running a OLS regression on household wealth (which can have negative values) for families with children using a single dummy variable x (1=single parent; 0=couple parents). I am using inverse ...
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Clarification on likelihood maximisation

From Eisenstein Natural Language Processing textbook, a discriminative log-linear model is defined as $$p(y|x,\theta) = \frac{\exp(\theta^Tf(x,y))}{\sum_{y'} \exp(\theta^Tf(x,y'))}$$ To estimate the ...
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Hessian of log-linear models and intuition

Im considering the log-linear model defined as $p(y|x,\theta) = \frac{1}{Z(\theta)}\exp(\theta f(x,y))$ where $Z(\theta) = \sum_{y'} \exp(\theta f(x,y))$ is the normalizer and $f(\cdot)$ is a feature ...
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Interpret coefficients in Log-linear model with variable in percentage

Excuse me, I have this equation LnY = 5.733−0.001𝑋1 + 0.075𝑋2, where Y is the number of patients in a province and my variable X2 is the percentage of homes that have water in a certain province ...
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Log-linear and GLM (Poisson) regression

I am afraid I am asking a stupid question... but... I would like to study the spending (my outcome variable) of a company by department, number of staff, activity, etc. I have collected my data and ...
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Using Log-Linear Regression to calculate the growth rate

I am learning the formula of growth rate and how to calculate this Growth rate is $y = a * (1+x) ^ b$ Log-linear regression: $log y = log_a + b * log (1+x)$ Then b is considered as coefficient What I ...
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What is the best way to test of draws ( 10,000 unique possibilities) from multiple sample are random?

say I have 6 people drawing from their own box, each box contains 10,000 unique barcodes. Now at the end of the experiment each person has drawn roughly 10-20 barcodes. How do I test if the barcodes ...
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log-linear model in R under multinomial scheme

I am trying to fit a log-linear model. In short, we can fit a log-linear model when family=poisson in R. But when we condition on N, we have multinomial ...
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Interpreting dummy coefficients in log-log linear model

I've been doing some log-log models and I've come across a problem in how to explain some of its coefficients, namely the dummy variables ones. In my particular case, my dependent variable is observed ...
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Scale Parameter in a Log-Linear Accelerated Failure Time Model

Let the logarithm of the random varible $T_i$, associated with the lifetime of the $i$th individual in a survival study, follow the disitribution $$log(T_i) = \mu + X_i\beta + \sigma\epsilon_i$$ with $...
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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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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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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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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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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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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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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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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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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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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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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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2 votes
1 answer
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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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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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2 votes
1 answer
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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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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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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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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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2 votes
2 answers
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Interpretation of $\beta$ 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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How to interpret the interaction coefficient of log-linear saturated model for a 3x3 table

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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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1 answer
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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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1 vote
1 answer
2k 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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3 votes
1 answer
1k 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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