Questions tagged [interpretation]
Refers generally to making substantive conclusions from the results of a statistical analysis.
827
questions with no upvoted or accepted answers
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Physical/pictoral interpretation of higher-order moments
I'm preparing a presentation about parallel statistics. I plan to illustrate the formulas for distributed computation of the mean and variance with examples involving center of gravity and moment of ...
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How do sufficiency statistics help in the interpretation of regression results?
One of the results why canonical link functions are widely used in GLMs is the existence of sufficiency statistics for the regression parameters, which in turn allow for:
... minimal
sufficient ...
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Principal components: Can I interpret PCA as essentially a change of basis
I was hoping that someone could simply validate or correct my interpretation of Principal Components Analysis. There are a lot of questions on this site about Principal Components analysis--some ...
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Interpretation of glmmPQL() spatial autocorrelation output
I am modeling binominal data with random effects and spatial autocorrelation using MASS::glmmPQL().
Plotting the residual semivariogram of a model fit without ...
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Interpreting odds ratios less than 1 with 3-category outcome
I have a 3-category ordered outcome (food consumption: 1=no food, 2=less food, 3=more food) and a 3-category ordered predictor (food exposure: 3=no time, 2= less time, 1= more time- whereby 3=no time ...
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Interpretation of smoothing spline
This question is about interpreting the results from non-linear regression models, especially when using regression splines. The numerical output is not very informative when interpreting the effects, ...
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Interpretation of biplot in PCA
Blue points all appear in the lower right-hand quadrant in the plane formed by the first two principal components.
Is it a good interpretation of the biplot (right panel) to say that blue points are ...
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Geometric Interpretation of Softmax Regression
I'm writing a series of blog posts on the basics of machine learning, just for fun, mostly to validate my understanding of Andrew Ng's class. As I'm currently studying generalized linear models (GLMs),...
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Interpreting SHAP Dependence Plot for Categorical Variables
I'm reading about the use of Shapley values for explaining complex machine learning models and I'm confused about how I should interpret the SHAP independence plot in the case of a categorical ...
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Segmented regression in R: interpreting the other coefficients
I am running segmented regression using the R package 'segmented'. The original binomial logistic regression has two coefficients, approach_km (continuous), and sea (dichotomous) that explain the ...
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Adjustment in a regression for community level aggregation of individual level data
In a cross-sectional study based on geographical multilevel regression, the authors used both individual-level data AND features generated by aggregating the same individual data in the community and ...
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Brief characterizations of AIC and BIC: how helpful are they?
I have found the following one-sentence characterizations of AIC and BIC in a lecture note:
AIC estimates the degree to which the predictive accuracy of the model will generalize to new data.
BIC ...
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Help with using variables as ordered factors/how to read lme4 output
I am quite new to R and also to LME statistics and would greatly appreciate any help. I am trying to figure out whether I have changed the variables in my study accordingly, and how to read the ...
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Interpreting Random Effects for Poisson GLMM
There seem to be a few answers for normally distributed models, but after some searching I could only come across this page for Poisson mixed models. I want to be certain I am interpreting the random ...
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Interpreting the variance of random effects in Mixed Linear Models?
When fitting the following simple model, using the 'lme4' R package and including a fixed and random slope term, I get:
...
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How do I interpret the random intercepts of a multilevel mixed-effects model?
I am using a three-level mixed-effects model in which:
individuals (level 1) are nested in
primary sampling units (PSUs) or enumeration areas (level 2) which in turn are nested in
countries (...
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Determining the effect of number of likes
Let's say I have marketing data and I need to determine how effective the marketing is. The marketing strategy is to publish facebook posts at inconsistent intervals.
The goal is to see how the ...
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Interpreting MANOVA and redundancy analysis of a canonical correlation analysis
I have done a canonical correlation analysis using the American Community Survey Dataset. The analysis is done between Ancestry and ...
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Confidence interval for proportions
I have some data like this:
id pop var
1 593 51
2 592 31
3 346 20
4 1214 70
5 1063 66
6 1370 71
each ...
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Is this interpretation of prediction intervals correct?
I have a regression model relating to a ''normal'' population. If a new observation which corresponds to point $x$ is outside the prediction interval at $x$, do I have a reason to suspect the new ...
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Scale of the correlation coefficient: is "r = .40 is twice as strong as r = .20" allowed/correct?
Some people recommend the following procedure to calculate the mean of several correlation coefficients: transform the coefficients by Fisher's $z$ transformation, calculate the mean of that, and ...
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When interpreting machine learning models, should preprocessing steps be considered as part of "model"?
Suppose I have some inputs on which I first apply some feature engineering and then apply a machine learning algorithm such as random forest to make predictions.
Now, if I want to interpret/explain ...
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Is it okay to ignore concurvity on our GAM model?
I'm trying to model a relationship between marine debris concentration (item/m^2) with several covariates using GAM with MGCV R package. I found that the concurvity values at worst-case scenario are ...
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Best textbook on philosophical background of interpretations (for beginners)
I'm looking for the best textbook teaches basics of statistics for a general researcher (undergraduate) without totally ignoring the mathematical proofs and theories while the main emphasizes is on ...
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GP: How to select a model for a classification task, based in overall accuracy and log-marginal likelihood?
I have fitted a Gaussian Process (GP) to perform a binary classification task. The dataset is balanced, so I have an equal number of samples with 0/1 label for the training. The covariance function ...
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What are the benefits of the z-score interpretation of probit regression coefficients?
Logit vs. probit is often a big debate. Many prefer logit simply because the coefficients can easily be converted into odds ratios, which are "more intuitive" to interpret than the z-score ...
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Ordered logistic Regression with categorical variables
I am conducting a regression. There is an ordinal dependent variable (ordered from 1 to three) and some categorical independent variables (each of them includes several items).
I adopted the ...
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4
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all regressions: coefficients interpretation
good morning to all, I open this topic with the intention of being useful to me but also to many in my situational. I would like to clarify the "interpretation" of the coefficients in the regression. ...
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What do the outputs of my zero inflated poisson model mean? (counts of fish)
I am looking a counts of fish within different size classes (0-10, 10-20 etc) between 3 different reef sites, 3 different depths and 2 different survey methods. However, naturally on all observations ...
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How to interpret lsmeans output for my lmer model?
I've defined an lmer model in R with 2 fixed effects, 2 random intercepts and a random slope:
...
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Interpretation of log transformed predictor in negative binomial regression
I mainly want to make sure that I'm making the correct interpretation here.
I built a negative binomial regression model predicting a count variable. There was evidence of overdispersion or I would ...
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Interpretation of clogit coefficients (Survival package in R)
Still very very new to R! I've run a conjoint (choice) experiment that uses the function clogit. Output as follows: (this model has been obtained through stepwise methods)
...
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Interpretation of mixed model with repeated measures
I have performed the following experiment: Two genotype groups of two different ages were monitored in the presence of three drugs one after the other. So, each subject after a control period received ...
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Difference beween supplementary and active variables in PCA - Interpretation on obsevations?
I would like to introduce two supplementary variables into a PCA I'm conducting on a set of data measuring concentration in different material phases.
However I'm unclear as to how to interpret the ...
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Interpretation AFT, Cox PH and discrete-time hazard model
I am struggling with the interpretation of the AFT model, Cox proportional hazard model and discrete-time hazard model.
My question is:
Can the coefficients in discrete-time hazard model also be ...
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GEE (or GLMM) in SPSS: Interpreting outputs and model selection
I am attempting to analyze my (experimental psych) data in SPSS, and I have a few questions regarding the kind of analysis I should be using (GEE or GLMM), how I should be interpreting the output, and ...
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Comparing results to 50% chance with ANOVA
I've been having a difficult time looking for a solution to this one, though it seems easy enough. I'm trying to replicate an experiment (Fukumura, van Gompel 2010, JoMaL) which was constructed as ...
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1
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What is "explained" by the explained/regression sum of squares?
We are in a regression setting. Let's start by defining some notation and terminology.
$y_i$ is observation $i$ of some (response) variable $Y$.
$\hat{y}_i$ is the value of $y_i$ predicted by a ...
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How to interpret coefficient and marginal effect in probit when $\beta$ is not identified
Say we have the latent variable $y_i^*=x_i\beta-\epsilon_i$ and $\epsilon_i \sim N(0, \sigma^2)$.
$y_i^*/\sigma=x_i\beta/\sigma-u_i$ where $u_i=\epsilon_i/\sigma \sim N(0, 1)$, and so can use Probit ...
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Interpreting logistic regression interactions predicted probability versus logit
I have a logistic regression, and I am interested in the interaction between two categorical variables: one (let's call it A) is a continuous variable categorized in 20 quantiles, the other (B) is a ...
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1
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Interpret multiple logistic regression
I have two groups of patients who were part of an intervention many years ago, and some covariates about their characteristics e.g., age, BMI, and years since the intervention. I have conducted a ...
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3
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Feature importance: t-value vs coefficients
I am estimating a logistic regression and I would like to know the feature importance of each variable. As far as I know, there are two possible ways to get it:
Estimate a logistic regression with ...
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Presenting result of bivariate regression to general public
We have a simple unvariate linear model of woodpecker abundance vs elevation:
woodpeckers ~ elevation
The model reports significantly positive slope for elevation. ...
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Why should we interpret a high order interaction (e.g. > 3-way) by only conditioning on 1 of the factors?
lets consider now we have conducted a 3-way anova and found a significant 3-way interaction effect A:B:C. As far as I am reading from textbooks/this website, the general suggestion is that we should ...
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How to interpret NRMSE (Normalised Root Mean Square Error) without comparing models?
I have fitted some robust mixed effects linear regression models (using robustlmm::rlmer in R).
I have calculated the normalised root mean square error (NRMSE) for these models but I want to make sure ...
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Can I validate a residual plot although it has residual patterns if I am not interested in model's coefficients using `lme4::glmer()`?
I am studying how well I can predict the height above ground (km) of an animal (=bird) using a technique (method B) which samples data every certain time-intervals. ...
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Regression methods for different sizes of $n$
I thought about something interesting today.
Suppose we have a regression problem where the relationship between the response and the predictor variables is approximately linear.
Let $n$ be the ...
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Interpretation of sampling distribution as the main distinction between Bayesian and classical statistics (Leamer)
In Hendry et al. (1990) p. 187-188, Edward Leamer says:
To me the essential difference between the Bayesian and a classical point of view is not that the parameters are treated as random variables, ...
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