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 ...

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9 views

What effect, if any, do outliers have on mediation analysis with bootstrapping?

I am running a mediation analysis spread over 6 models. Analysis is performed using the PROCESS macro. Each model includes 1 IV, 2 parallel mediators, and 1 DV. In a couple of the IVs, a number of ...
0
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0answers
34 views

Is my sample suitable for elastic net? What are the assumptions?

I was hoping to use multiple regression to identify significant predictors but I have a tiny sample size (group 1 n=9, group 2 n=37) so I'll be unable to do this. I have read that regularisation ...
3
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2answers
153 views

What causes non-normality of the error term in OLS?

In data, what causes the error term to be non-normally distributed in regression? Along the same lines, what solutions are there for non-normal residuals? For example, is it caused solely by a ...
2
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0answers
23 views

Cox Proportional Hazards Assumptions - Simplest Tests in R

I have no stats background, and have been looking into Cox models. $$ h(t) = h_0(t)e^{\beta_1 x_1 + \beta_2 x_2 + ...}$$ (Where $h$ is an individual hazard function, $h_0$ is the baseline hazard ...
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3answers
76 views

Counterexample against binomial assumptions

The question is from a Master-level Probability Course. It is well known that the underlying assumption for the binomial distribution is that there are n independent Bernoulli trials. More ...
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2answers
31 views

Simulating violations of regression assumptions

I'm wondering if anyone could provide some code (preferably in R) which demonstrates violated assumptions leading to type 1 errors. Some concrete examples of errors arising from assumption violations ...
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0answers
39 views

How to make assumptions about the measured data

I just finished a 1-yr continuous measurement of the hourly concentration of air pollutants and environmental influencing factors, such as temperature, relative humidity etc. For the next step, I ...
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2answers
166 views

Why do we have to assume normality for a one-sample t-test?

As a consequence of the central limit theorem the sampling distribution of the sample means will always be normal whatever is the distribution of the variable we measure. From our sample we can ...
3
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0answers
86 views

What does “independent observations” mean?

I'm trying to understand what the assumption of independent observations means. Some definitions are 1 "the occurrence of one event doesn't change the probability for another". 2 "sampling of one ...
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0answers
9 views

ANCOVA: what do I do when my covariate and DV do not correlate?

I was planning to use an ANCOVA for my study, however, the CV and DV do not correlate. In this case can I instead use an ANOVA?
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26 views

Need to transform data before running mediation/model with bootstrapping (PROCESS)?

I am reading through Hayes' book on mediation and moderation analysis (2013) which describes the PROCESS macro he created to use bootstrapping in order to arrive to confidence intervals to check the ...
2
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2answers
102 views

Importance of multiple linear regression assumptions when building predictive regression models

As far as I know, one can differentiate between two main goals of the regression analysis: The goal is understanding causal relations between variables. Here, one has to check several common ...
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1answer
23 views

Rules of thumb for PERMANOVA

I'm currently assessing the best option for looking at some community composition data, and determining how they differ among locations. Ultimately, as I'm simply looking to see if there is a ...
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0answers
20 views

Struggling with non-normality in generalized linear model

Dear statistics experts, I am looking for correlations between certain measures of brain structural integrity (fractional anisotropy, given as ratio between two hemisphere ==> rational data range ...
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0answers
13 views

ICC to assess independence of observations in a cluster randomized trial

How can I compute an ICC to assess independence of observation assumption using SPSS for ANOVA. The data on two DVs were collected from participants one time over 28 weeks in 28 clusters (so this is ...
1
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3answers
49 views

In ANOVA, if the null hypothesis is true is the expected value of F guaranteed to be 1?

By null hypothesis is true I mean that the means of each group is the same at population level. I am wondering whether the expected value would depart from 1 in the case that the variances of the ...
2
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1answer
70 views

GLM regression - help choosing model specification

I think I need to use a Poisson-family regression or negative binomial regression. My variables are as follows: Y is an integer value ranging from 0 to ~1200. It represents sums (number of species ...
3
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1answer
61 views

How to assess the proportional hazards assumption for a continous variable

I am having a problem with checking the assumptions for a continuous variable in a proportional hazards model. If a variable were a factor with many levels, then I could use the logrank test or check ...
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0answers
38 views

Model assumptions and diagnostics for proportional hazard regression model with frailty in R

I am wondering are there any assumptions that must be met in the proportional hazard regression model with frailty? I remember that in regular proportional hazard model without frailty all variables ...
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0answers
18 views

How to eliminate dependent inputs?

There are a lot of statistical methods that rely on the assumption of input independence. For example, Naive Bayes text classifiers operate under the assumption that occurrences of different words are ...
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1answer
65 views

Does Fisher linear discriminant analysis (LDA) require normal distribution of the data in each class?

Does Fisher linear discriminant analysis really require the data distribution in each category to be normal? I see two versions. The first one states that it requires the normal distribution and ...
2
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1answer
47 views

If my normality test is non-significant, am I safe to use the t-test?

I took a 30 unit sample from a population. The sample distribution resulted to be normal. Can I state that the population distribution is normal too? If so, with what level of confidence?
2
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2answers
71 views

Objective test for proportionality assumption in Cox Regression Model (SAS)?

I was trying to fit Cox Regression (aka Proportional Hazard) model on some cancer data (N=2288). I got the following output from SAS proc phreg: ...
2
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1answer
71 views

What’s wrong with this way of fitting time-dependent coefficients in a Cox regression?

I have a Cox proportional hazards model. Judging by Schoenfeld residual vs. time plots and corresponding tests for zero slope, there is clear violation of the PH assumption for several of the ...
3
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0answers
37 views

Partial regression plots vs scatter plots for checking linearity

In a multiple linear regression analysis, what is the most suitable plot for checking linearity? I have seen a number of examples that use scatterplots as a preliminary test to use a linear model. ...
3
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0answers
112 views

Significant output in Levene's test for equality of variances in MANOVA; what to do?

I want to perform a MANOVA in SPSS as follows: i have a independent variable that consists of three groups (- of which the group sizes are not equal), and six dependent variables. When checking the ...
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0answers
22 views

web analytic: average session length based on visits numbers per minute

At hand, I only have the number of visits per minute for one web page (one day period), is it possible to generate the average session length of such page based on these numbers? Or and references I ...
1
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1answer
21 views

Assumptions of two way anova

Please tell me what the actual assumptions of a two way anova are. I read somewhere that this being similar to multiple regression, the only assumption is that the residuals are to be normally ...
4
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1answer
71 views

Working with residuals of regression

So the background is that the I collected yield data for past 5-6 decades and location from where I collected yield data had high yielding varieties introduced over time. I am looking at the ...
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1answer
47 views

Is it necessary to plot histogram of dependent variable before running simple linear regression?

I was working on an assignment. The data set was really simple, only consisting one independent variable $y$ and dependent variable $x$. Someone suggested me plot a histogram of $y$ before running ...
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0answers
42 views

How do I test for homogeneity of regression in MANCOVA?

I am using a one-way independent MANCOVA with 4 dependent variables and a single covariate. My predictor is bivariate. I'm currently trying to test for heterogeneity of regression in SPSS by ...
4
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2answers
87 views

Two simple questions regarding GLM

I'm currently doing a modelling project. However, I haven't taken a bunch of statistics classes, so I have to teach myself generalized linear models. I'm reading Generalized Linear Models for ...
2
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1answer
43 views

Assumption for valid hypothesis testing of the OLS estimators in the small samples

Please support me solve this question: In a simple regression model y = b0 + b1*x + u we have the five main assumptions 1 linearity in parameters 2 random sampling 3 zero conditional mean 4 variation ...
1
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1answer
75 views

R - Test for homogeneity of regression slopes results in singular model

I am trying to check the assumptions of a two-way ANCOVA. So in my model I have two factors (F1, F2) one dummy coded two level covariate (C) one dependent variable (D) In order to check the ...
0
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0answers
33 views

How to check discriminant analysis assumption in R using lda?

I want to use lda in MASS package in R. According to the theory behind that, first need to validate the assumption. Actually I've found some example from the net but they did not bother to validate ...
4
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1answer
111 views

2x2 ANOVA - assess violations of homoscedasticity & normality

I have a 2x2 factorial unbalanced between-subject design, n = 355. My DV is a subjective probability estimate (i.e., a number between 0 and 100). My ANOVA model: ...
6
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2answers
188 views

Heteroskedasticity in residuals vs. fitted plot

I am testing whether price per ounce of beer (continuous variable, range of values mostly between 0.1 and 0.5 dollars) and the presence of promotion, advertisement, and display (all binary) have ...
10
votes
2answers
321 views

Are normally distributed X and Y more likely to result in normally distributed residuals?

Here the misinterpretation of the assumption of normality in linear regression is discussed (that the 'normality' refers the the X and/or Y rather than the residuals), and the poster asks if it is ...
3
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2answers
568 views

Logistic regression assumptions for a model with many binary independent variables

I am working on developing a logistic regression model that uses qualitative variables only ($n=990$). My remit is to define the equation that can identify the most relevant characteristics of a ...
4
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0answers
76 views

Model assumptions of partial least squares (PLS)

I am trying to find information regarding the assumptions of PLS regression (single Y). I am especially interested in a comparison of the assumptions of PLS with regards to those of OLS regression. ...
0
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0answers
30 views

Discarding the violation of homogeneity of variance in ANOVA

If after a bartlett.test(split(x,list(f1,f2))) I get a very significant p-value, but my sample size is huge -- millions of measurements -- is it justified to ...
0
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1answer
45 views

When reporting a CFA, is it desirable to assess univariate normality in addition to multivariate normality?

I am using SPSS AMOS to do a factor analysis and it produces statistics related to both univariate and multivariate normality. p35 of the AMOS Users Guide states that "[T]he observed variables must ...
5
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1answer
185 views

Does testing for assumptions affect type I error?

I just performed simple simulation. Made two "populations" with different means and the same variance. Since I prepared them I know that they: are normal, differs in location and both have the same ...
4
votes
3answers
465 views

Assumptions of linear models and what to do if the residuals are not normally distributed

I am a little bit confused on what the assumptions of linear regression are. So far I checked whether: all of the explanatory variables correlated linearly with the response variable. (This was the ...
2
votes
1answer
94 views

Do these residual plots violate the linearity and homogeneity assumptions for linear regression?

There seem to be too many points clustered around negative values for all the plots And while 3 & 4 seem to have random enough patterns, 1 & 2 seems to have negatively sloped trend. If ...
1
vote
1answer
103 views

Why does poisson regression need to assume observations are poisson distributed?

Zuur (2013) 'Beginners Guide to GLM and GLMM' states that if the Pearson residuals, when plotted against fitted values from a poisson regression, show the pattern below then the assumption of poisson ...
2
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1answer
97 views

Consequences of non normal-distribution multiple regression

I am currently writing my thesis using multiple regression. However my data does not meet the regression assumption of normal distribution. I want to describe that, due to the non normal ...
0
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1answer
117 views

What makes the results differ for fixed-effects models vis-à-vis random effects models?

What makes the results differ for fixed-effects models vis-à-vis random effects models? The Cochrane Collaboration's website indicated that two models can produce different results for a meta ...
10
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4answers
487 views

Practically speaking, how do people handle ANOVA when the data doesn't quite meet assumptions?

This isn't a strictly stats question--I can read all the textbooks about ANOVA assumptions--I'm trying to figure out how actual working analysts handle data that doesn't quite meet the assumptions. ...
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0answers
47 views

Forecast accuracy – can we use correlation and $t$-tests?

Does it make sense to compare actual vs. forecast using correlation analysis / see how close $R^2$ is to 1? Does it make sense to use a paired t-test to test actual vs. forecast to get accuracy of ...