# Tagged Questions

Refers to the conditions under which a statistics procedure yields valid estimates and/or inference. E.g., many statistical techniques require the assumption that the data are randomly sampled in some way. Theoretical results about estimators usually require assumptions about the data generating ...

142 views

### Does a confidence interval carry some extra error for non perfectly normal distributions?

I'm not trying to nitpick but I always want to make sure with stats that I clearly understand the delimitation between exact/theoretical measurements and "real life" measurements. Let's say for ...
15 views

### Generalised Boosted Models (GBM) Assumptions

I have a rather simple question the answer to which I struggle to find in any literature about GBM. I am fitting a GBM model as per G.Ridgeway (2007), paper can be found in http://www.saedsayad.com/...
10 views

### Negative binomial regression: control variables

Question: what are the assumptions of a negative binomial regression? Do continuous control variables (the DV and main IV are binary) need to follow a normal distribution? I have been searching online ...
11 views

### In practise, How important is linearity and goodness-of-fit in logistic regression?

In my field of study, logistic regression is commonly used. Linearity of the log odds and the independent variable is one of the assumptions to logistic regression. In all types of regression analysis,...
34 views

### What are the assumptions to path analysis and how to test them?

There are some structural assumptions to path analysis that are not difficult ascertain. They are (a) no loops (b) no going forward and backward (c) a maximum of one curved arrow per path. I am aware ...
27 views

### Which assumptions do I need to check for a GLMM with a binary response (and how?)

I am modeling binomial responses using Generalized Linear Mixed Models with a nested random effect (not of interest, simply a control: year nested within location) and both categorical, count, and ...
17 views

### Assumptions for PCR and PLS

I am writing up a report on fitting Principal Component Regression (PCR) and Partial Least Squares (PLS) to my data-set. A similar question: Model assumptions of partial least squares (PLS) ...
32 views

### Performing a t-test with discrete (currency) data

I want to perform a 2 sample t-test assuming unequal variances, however my variable is currency. Currency is discrete, however when checking the assumptions of the t-test, I see that the data should ...
4 views

### Greenhouse-Geisser correction vs Non-independence

In repeated-measure ANOVA, Greenhouse-Geisser correction is commonly used to handle sphericity issues (when there are more than three levels in a condition). But does it deal with data that violate ...
197 views

28 views

### Does Naive Bayes assume normality?

I came across this paper about Naive Bayes that states [Naive Bayes] is based on another common simplifying assumption: the values of numeric attributes are normally distributed within each class. ...
50 views

### ANCOVA for 2X2 crossover with baseline measurements - validity of assumptions

I'm trying to learn how to do ANCOVA for a 2x2 crossover study with baseline measurements. I have followed the analysis performed at Mehrotra 2014 "A recommended analysis for 2 x 2 crossover trials ...
14 views

### Using raw residuals rather than standardized residuals for Q-Q/P-P plot and residual vs fitted plot

When I was doing my undergraduate studies, I remembered that my lecturers usually uses raw residuals to obtain the plots mentioned above. Some books that I have also used raw residuals. However, ...
14 views

### Checking linearity assumption and colinearity assumption

Linear regression is equivalent to ANOVA. Do we need to check for linearity and multicolinearity for ANOVA? I have seen that these assumptions are usually omitted for ANOVA but not for linear ...
23 views

### Measure relationship between continuous variable & unbalanced binary variable

I am trying to select variables for modelling a binary variable (whether a person will repay a loan) using various continuous variables about them - age, income, years of education, etc. I'd like to ...
22 views

### VIF interactions

I would like to check for multicollinearity in logistic regression analysis. Independent variables are categorical (always binary) and continuous. Sample has limitted size (N=176, 36 events), so I can ...
55 views

### Can logistic regression be used with “years” as a continuous variable?

We are currently collecting data for a study whose purpose is to show whether scientists are focusing more or less on a specific subject with time. To keep some privacy let's say the subject is jelly ...
52 views

### How to check permutation testing exchangeability assumption when using a General Linear Model

I have a question on the assumption of exchangeability in permutation tests. Although I read a lot about this topic, I am still confused. For $N$ subjects, I have the value of a clinical measure $Y$ (...
33 views

### Fisher and chi-squared assumptions/limitations not met

Fisher exact test is said to be used with a total sample (n) < 1000, whereas chi-squared test should be used when each category (/cell in a contingency table) >=5. What if you have an mxn ...
9 views

### Why do we need to check for these two assumptions for ANCOVA but not for factorial ANOVA?

ANCOVA has two additional assumptions as compared to two-way factorial ANOVA. They are (1) independence of the covariate and factor (2) homogeneity of slope. Why don't we need to check them for two-...
27 views

### Does the unconditional distribution of $y_i$ only depend on the distribution of the errors?

In linear regression, does the unconditional distribution of $y_i$ only depend on the distribution of the errors? For example, is it not the case that if $$y_i = \beta_0 +\beta_1 x_i + u_i$$ and ...
36 views

### predictor skewed but normality of errors

In linear regression (linearity assumption had been checked), what is the effect if distribution of predictor is skewed but errors are normally distributed? Is there a risk for estimation of ...
27 views

### Why is the “sphericity assumption” in RM-ANOVA (constant variance of difference scores) called “sphericity”?

Why is the "sphericity assumption" in RM-ANOVA, i.e. the assumption of constant variance of difference scores, called "sphericity"? (This question was suggested in the comments to a related question.)...
93 views

### help for interpreting the residuals vs. fitted values plot

I have an ordinal variable (scale of stress) considered as continuous predictor in a multivariate linear regression. I would like to verify the assumption of linearity and this is my residuals vs. ...
21 views

### In testing Heteroscedasticity, when should I use Park Test or Glejser Test?

I am currently running a data analysis on survey data. In testing the heteroscedasticity assumption in Multiple Linear Regression, using Park Test, the research actually passed the test. However, when ...
21 views

### When are observations not weakly exchangeable?

In the book "Common errors in statistics", I read the following statement Permutation tests only yield exact significance levels if the labels on the observations are weakly exchangeable under ...
8 views

### Is it meaningful to look at predicted values vs residual plot to assess homogeneity of variance assumption for mixed ANOVA?

I have two-way mixed ANOVA. I remembered getting the a single value predicted values when I plotted predict vs residual plot for one-way repeated measures ANOVA. So is it meaningful to produce the ...
344 views

### Regression: why test normality of overall residuals, instead of residuals conditional on $\hat{y}$?

I understand that in linear regression the errors are assumed to be normally distributed, conditional on the predicted value of y. Then we look at the residuals as a kind of proxy for the errors. It'...
48 views

### How to deal with failing the proportional odds assumption in ordinal logistic regression

I am attempting to do ordinal logistic regression but I keep failing to pass the proportional odds assumption. Almost all of my features are shown to have high significance, but the only model that I ...
130 views

### Goodness of fit test on sparse contigency tables with high dimensionality

I have a vector of size 1x3500, which can be viewed as the 'known distribution'. It is simply a table of counts across 3500 groups (i.e. a contingency table). I also have $N$ other vectors of the same ...
52 views

### Zero Inflated Versus Negative Binomial Models Conundrum

I have a count variable that represents the number of new band foundings in a country-year. However, there is zero inflation as there are no foundings for most country-year. There is also ...
31 views

### which variables should I include in a multiple regression analysis?

From what I understand, one should only include an independent variable in a multiple regression analysis if it meets the assumption of linearity. I have six variables, three of which are correlated ...
83 views

### Omitted variable bias and the constant term

For omitted variable bias to occur when a variable is left out of a regression, there is one axiom and one condition that must be fulfilled: (Axiom) By definition, the coefficient of the variable ...
122 views

### What to do first when there are violations of assumption in Simple Regression? [duplicate]

Suppose we want to do simple linear regression. Before we do simple linear regression, we need to check these following assumptions (please correct me if I'm wrong): Linear relationship Normality of ...
88 views

### The distinction between stochastic independent variable and measurement error in independent OLS variable

Assume that OLS regression of the form: $$Y_t = X_t'\beta + u_t$$ Suppose $X_t$ are stochastic, thus standard Gauss-Markov assumptions need to be accommodated. Given that: \text{E} {(\hat\beta)} ...
13 views

### Unequal levels of independent variable in regression with non-randomized groups

I'm running a multivariate regression (multiple continuous DVs) that also has multiple predictors (1 two-level categorical, 1 continuous). The categorical predictor is the group participants were in, ...
38 views

### For what classes of models is the assumption that the residuals sum to zero relaxed?

My question is related to an interesting suggestion about relaxing OLS assumptions by @alexis back in May 2014: Assumptions of linear models and what to do if the residuals are not normally ...
676 views

### Do we really need to include “all relevant predictors?”

A basic assumption of using regression models for inference is that "all relevant predictors" have been included in the prediction equation. The rationale is that failure to include an important real-...
585 views

### Does the assumption of Normal errors imply that Y is also Normal?

Unless I'm mistaken, in a linear model, the distribution of the response is assumed to have a systematic component and a random component. The error term captures the random component. Therefore, if ...
82 views

### Why can we assume normally distributed errors in probit but not in LPM?

Why are we able to assume normally distributed errors in probit models but not in linear probability models (LPM)? When used with a binary dependent variable, LPMs violate a few necessary assumptions....
164 views

### Does leaving out an important predictor in a mixed linear model violate the independence assumption?

I have data from an experiment with 3 groups, measured at 4 time points, where each subject performed a task where 2 factors are manipulated: valence (3 levels) and predictability (2 levels). I know ...
23 views

### When creating a multiple regression model for a subgroup, is it necessary to test all assumptions again?

My results section consists of a multiple regression analysis considering 3 factors, containing all of my participants. Following this, I have considered males and females separately, by construction ...
51 views

### Controlling for individual in nlme when most individuals only measured once

I am trying to model growth using nlme for a number of individuals over four time periods. My question is, did growth differ over time? Some individuals were measured twice or more, perhaps as a young ...
27 views

### Are linear regression errors independent? Mean independent? Uncorrelated?

All I know is that we assume zero conditional mean (and hence zero mean) and conditional homoscedasticity (and hence homoscedasticity). When trying to prove that \$E[(\hat{\beta_1} - \beta_1)\bar{u}] =...
17 views

### Assessing the residual independence assumption (nonlinear least squares regression diagnostics)

I would like to assess the assumptions underlying nonlinear regression models using statistical tests rather than graphical methods since I have thousands of fitting results. I am not certain ...
85 views

### When is it OK to write “we assumed a normal distribution” of an empirical measurement?

It is ingrained in the teaching of applied disciplines, such as medicine, that measurements of bio-medical quantities in the population follow a normal "bell curve." A Google search of the the string "...
58 views

### Is being the first-born independent of age?

If one were to assert that, in a large population, the fact of a person or an animal being the first-born in the family was independent of their age, then what assumptions (if any) would one have to ...