Questions tagged [interpretation]

Refers generally to making substantive conclusions from the results of a statistical analysis.

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VECM Cointegration Relationship Coefficient(s) Interpretation [duplicate]

Theory dictates that when there is one cointegration relationship, it's coefficient in a VECM must be statistically significant and negative to maintain the long-run equilibrium. Nonetheless, when ...
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LIME Analysis Linear Model

I am looking at explaining a single prediction for a linear model: Y = F(X) = x0 + a1x1 + a2x2 + ... anxn i.e. F: X -> Y i.e. given a single instance z in X, ...
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White box/ interpretable model

I am looking for classification/ regression methods that could be considered "white box" models, meaning they have some degree of interpretability or "can be explained". My dataset has 16 dimensions ...
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1answer
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Confused on how to interpret ZINB and Hurdle models

Below are a set of results from a zero-inflated (AIC = 64992.15; BIC = 65280.78) and hurdle model (AIC = 65141.73; BIC = 65430.36) for a dataset (>18000 obs) which describes the number of illicit ...
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How to interpret cross-over moderation?

I have these simple slope analysis graphs, are both cross-over moderation? and how to interpret each one? Thanks.
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Interpretation of interaction term in negative binomial Difference-in-Differences regression

I have a question regarding how to interpret an interaction term in a negative binomial Difference-in-Differences (DiD) regression. I use the negative binomial as my dependent variable (crimes) is ...
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1answer
69 views

What to do when difference-in-differences affects covariates

Consider the model $y_{it} = \alpha_i + \beta_{it}did_{it} + \gamma_{it} + \phi_i + \zeta_t + \varepsilon_{it}$ for group $i$ and year $t$. $\phi_i$ refers to group fixed effects and $\zeta_t$ to ...
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Difference in joined or splitted random slopes in mixed model (lme4 notation)

I would like to understand better the consequences of formula syntax choices in lme4 package. Imagine I want to model outcome Y as a function of X1 and X2 = f(X1), with and without interaction, with ...
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Elastic Net scikit-learn: same model and input data but different prediction values

I was training an Elastic Net using scikit-learn and I bumped into the following problem. I am getting different prediction values for the same input data and model. What is happening? Am I missing ...
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How to correctly analyze fatality rate and daily deaths of Chinese and Italian COVID-19 outbreak?

This is a strange case of difference in fatality rate between Chinese and Italian covid-19 outbreak. In my knowledge, fatality rate is a ratio between deaths from a certain disease compared to the ...
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How do I introduce control variables in a regression where the I am comparing coefficients to the base?

I am running regressions where I need to compare the coefficients with the base, but I am a little confused about how to introduce the control variables. My regression looks as per: ...
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Interpretation of LM statistic and J-Bera statistic

How should I interpret the results of autocorrelation and normality from the tables enclosed herewith?
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Linear Discriminant Analysis classifier interpretation

Hi I am using Linear Discriminant Analysis (LDA) to solve binary classification problem. After fitting, I can get the projection matrix and class means. I am just wondering how can I turn that into ...
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2answers
55 views

Interpretation of Squared Variable [duplicate]

I did a multiple variable regression using R, for $Grade_i = β_0 + β_1(Hours_i) + β_2(Hours_i^2) + μ_i$, this is what I got: . But I'm having trouble interpreting the estimated value for $β_2$, ...
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1answer
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Interpretation of $\mathbf{w^{\top}Cw}$ [closed]

I'm reading a piece on portfolio optimization where it is stated that $\mathbf{w^{\top}Cw}$ is the variance of the expected return, where $\mathbf{C}$ is a covariance matrix and $\mathbf{w}$ is a ...
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1answer
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How to interpret the regression co-efficient of a particular variable in a negative binomial regression?

I have the following regression equation with a count variable as the dependent variable and diversity as the predictor. ...
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25 views

How do I interpret K-means model output from Pyspark ml. clustering library?

I am new to PySpark and learning how to build models using PySpark's machine learning libraries. I build a k-means clustering algorithm based on the code of this website. Now, I fed my data into the ...
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what is the difference between feature importance and global explanation of the model?

Feature importance means how much that particular feature supported to derive that particular prediction.global explanation means explains how the model behaves generally. but i need clear explanation ...
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Correlation of outputs in Bayesian hierarchical regression

I am using a Bayesian hierarchical regression (stan_lmer in rstanarm) to do a MCMC sample of the posterior for the mixed effects model y ~ A * B + (1|C). Although I have done other Bayesian ...
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1answer
24 views

Interpreting Y Outcome Variable when primary X is a proportion/ratio

I am currently starting with a simple regression whereas my outcome Y= raw student scores in an exam, while my X variable of interest is the ratio of substitute teachers in the school. I would truly ...
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Interpretability of the lasso coefficients

I have implemented the lasso method to a data set with 1000+ variables. I have reported the MSE value on the test set and the number of nonzero variables. I need to report the interpretability of the ...
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Multiple changes in statistical significance of predictor across steps in hierarchical regression - your insights please?

I have three IVs (A, B, C) and have entered them in three separate blocks (steps) in regression using SPSS. In step 1, Variable A independently predicts the DV. In step 2, after the addition of ...
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ARMA(-X) model with exogenous covariates interpretation

Let us assume that $Y_t$ can be described with an ARMAX process, including an exogenous covariate $X_t$, of the following form: \begin{equation} log(Y_t)=\phi_1log(Y_{t-1})+\phi_{12}log(Y_{t-12})+\...
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MANOVA output table interpretation

I am running a repeated measures manova on the effect of country (2 levels) on color-emotion interpretation ( I have 5 different colors, and 3 different emotions). I have never run a Manova before and ...
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Interpretation lm R independent categorical variable

I understand how to interpret dummy variables etc., but I have got trouble of interpreting a independent categorical variable. This is my output: ...
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How to interpret meta-regression results with significant moderators but no significant overall effect?

I'm conducting a meta-analysis where I have a given set of studies, each with multiple effects (correlations in my case) I'm interested in. Each correlation coefficient answers a different research ...
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Main effect significance disappeared after adjustment, but interaction still the same?

Hi I am confused by a result from my analysis. Could someone tell me is the situation possible? How can I interpret it? I have two linear mixed models, the data was from a family-based study. The ...
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Why am I seeing 0 degrees of freedom when testing main effects using lme4, but see 1 df when testing interaction?

So sorry if this is a dumb question, but I've been searching around and can't figure out what's going on. I'm running a mixed effect model with 2 fixed effects and random intercepts, as shown below. ...
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Interpreting Ordinal Independent variables when dependent is binary in Logistic Regression

I've searched the web deep and wide for an answer to my question. But there is little consistency to be found, which of course makes me very confused and thus leads me to asking here. I have a binary ...
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1answer
21 views

Getting unexplained negative coefficient in Logistic regression using SAS

I am using SAS in order to predict the probability that a borrower will default on his loan based on his age group. The variable age is divided in to 4 age groups. group 1 has 1315 customers and out ...
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1answer
141 views

Understanding and interpreting quantile regression

I am trying to better understand what quantile regressions are and how we can interpret them. I know that quantile regressions are used to model a specific conditional quantile $\tau$ of a response ...
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Ways to state relationships like “A explains x% the variation in B” but when variation is not present like for non-parametric tests

Example: Income explains 70% of the variance in expenditure. Variation in driving speed can be explained by drivers' age. How does one make such statements if the test used is a non-parametric one? I ...
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How should I label and interpret cumulative probability graphs

I've used R's empirical cumulative distribution function (ecdf) to generate a chart that shows the cumulative probability of some cost data. I want to know if the heading of the chart is correct or ...
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Interpretation of comparation of two dependent variables which have identical values

In theory I know statistical terms such as median, arithmetic mean, hi-square, etc., but how to interpret these terms if they are numbers like in the example. what does that mean ? ...
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Correct interpretation of coefficient estimates from GLM on binary outcome data [duplicate]

I'm currently analysing an experiment where animals were presented with a stimulus under two different treatments (Po & Br) ...
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Model adequacy test in curvilinear regression model

I've the idea regarding the model adequacy test of linear regression model. Curvilinear model being different from the linear model, how the model adequacy test of curvilinear regression model can be ...
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32 views

Interpreting results of multinominal logistic regression

I have run a multinominal logistic model with my dependent categorical variable, WINNING_PARTY, taking the following values: gov, corp, org, indiv, univ, or in part....
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Interpretation of Adjusted Predictions Contrasts (Margins)

I would really appreciate some help with interpreting results for contrasts of adjusted predictions (I use Stata 15, margins command). I run an experiment and fitted a regression model comparing the ...
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178 views

Interpret Interaction Effects in Negative Binomial Regression

I have two questions regarding the interpretation of interaction effects in a negative binomial regression model. The model uses the number of people arriving at a hotel per hour as the dependent ...
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1answer
56 views

Interpretation of mixed-effects versus GEE poisson/logit regression parameters

What's the difference in the interpretation of the model parameters (intercept +slope) in the mixed-effects model and GEE model for poisson and logistic regression?
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What does it mean when there exists a treatment group by time effect?

In longitudinal analysis, mixed-models, gee, what does it mean when there's a group by time effect as opposed to only a time effect and treatment group effect? What does treatment group effect signify ...
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What's the rationale behind a normality test followed by a $t$-test?

Correct me if I'm wrong, but from my understanding, the standard procedure of testing whether data from an unknown source have a specific mean is to (a) perform a normality test to see if the data are ...
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1answer
27 views

Interpretation question about between-subjects effects in multilevel modeling

Specific question that (of course) comes from a reviewer. In multilevel models with: Level2=individuals Level1=within-persons Is it fair to say that, since these models explicitly estimate Level 2 ...
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Can I use RMSE as a percentage of error

I'm hoping someone can verify my assumption. I am building a regression model against an outcome variable which is a percentage. After tuning, the model outputs an RMSE estimate which I've looked to ...
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Regressing predictions on corresponding observed values, does that make any sense? If so, would this be a reasonable proposition?

I have a list with around 100 different dependent variables, for each of them I have around 35 observed values with 12 explanatory variables (it’s the same 12 explanatory variables for all dependent ...
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What I can know about my probability distribution from the below hypotesis test table?

I have computed the distribution fit test of my probability distribution i got it 0 , then I have tried to creat the hypothesis data for that distribution I have got the below table , Now am not ...
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Interpreting standard errors of linear regression with logged dependent variable

I'm running a linear regression with a logged dependent variable. This is the only variable in the model that is logged. For interpretation, I've exponentiated the coefficients, subtracted one, and ...
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1answer
280 views

Interpretation of learning curves - large gap between train and validation loss

I am trying to train a neural network to predict the quality (good or bad) of produced parts based on the parameters of the production (31 parameters). The network is trained with 121620 samples and ...
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34 views

how to interprete this acf and pacf plots

I am trying to interpret ACF and PACF plots correctly, after simulating a 500 long chronological serie following the MA(2) model, I got these ACF and PACF plots , This this mean MA(2) Model is ...
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Orthogonal polynomials lme4: Interpretation of significant quadratic predictor when linear predictor is not significant [duplicate]

Summary of Study Participants worked in pairs to complete three tasks. Periodically throughout the interaction, they evaluated one another across a variety of categories. The primary category of ...

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