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

Checking the proportional odds assumption holds in an ordinal logistic regression using polr function

I have used the ‘polr’ function in the MASS package to run an ordinal logistic regression for an ordinal categorical response variable with 15 continuous explanatory variables. I have used the code ...
2
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1answer
105 views

Does the Mann-Whitney U-test require the groups to have the same distribution?

If one of my data sets is normally distributed and the other is not, can I do a Mann-Whitney U-test on them, or would they both have to be non-normal?
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13 views

Is 0 mean of residuals assumption crucial for every model?

I am writing a seminar paper about sales forecasting. I am doing couple of models and I am choosing which one gives the best forecasts (Decomposition method, SARIMA, Brown Exponential Smoothing, Holt ...
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2answers
124 views

How do residuals relate to the underlying disturbances?

In the least squares method we want to estimate the unknown parameters in the model: $$Y_j = \alpha + \beta x_j + \varepsilon_j \enspace (j=1...n)$$ Once we have done that (for some observed ...
2
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2answers
162 views

How to prove linearity assumption in regression analysis for a continuous dependent and nominal independent variable?

I want to check the assumptions for applying linear regression analysis. So, among others I check the linear dependency between my dependent (which is continuous) and my independent (nominal or dummy) ...
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1answer
68 views

Logistic Regression Assumptions

I am preparing a presentation on logistic regression. I applied logit model to a data set and now want to check whether my model meets logistic regression assumptions. I don't exactly know how to do ...
3
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2answers
112 views

What really happens when we transform the data using $f(x) = \sin(\sqrt{x})$?

I need to perform a two-way ANOVA on my data ($Y$: sleeping hours). My data is quite normal $p$-value = $0.07$ with Shapiro-Wilk test but when I run the normality test for my residual, $p$-value is ...
2
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0answers
10 views

Evaluating survival models in the presence of covariate-dependent censoring

I have a censored survival analysis problem with the following characteristics: Failure times are discretized The censorship distribution depends on certain covariates I don't have a ...
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1answer
53 views

Heckman 2-step Error Assumption

first question on StackExchange; thank you for having me. I am trying to really nail the intuition for the Heckman sample selection model. One little thing that is bothering me is the assumption ...
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0answers
21 views

Variance assumption and normal assumption not met, Kruskal or Welch-Anova?

I have 7 different groups of playing time data that is not normal. Lets say its really not normal..like a lot. The variance is also not equal and fails the bartlett test by a landslide. Sample ...
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0answers
25 views

Assumptions for nlme

I want to analyze a repeated measure design with two independent variables (var1, var2) where the subjects had to solve three ...
0
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0answers
12 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
44 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
194 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
27 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 ...
3
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3answers
83 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
34 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
40 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
179 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
140 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
10 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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0answers
42 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
votes
2answers
118 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
29 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
31 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
17 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 ...
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3answers
117 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 ...
3
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1answer
81 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 ...
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1answer
78 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 ...
0
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0answers
46 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 ...
1
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0answers
20 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 ...
1
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1answer
105 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
votes
1answer
49 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
101 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
83 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
45 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
votes
0answers
166 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 ...
0
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0answers
26 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
23 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
72 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 ...
1
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1answer
54 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 ...
1
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0answers
52 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
votes
2answers
103 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
votes
1answer
57 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
vote
1answer
111 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
41 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
votes
1answer
153 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
votes
2answers
242 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
339 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
714 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 ...