Questions tagged [r]

Use this tag for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.

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182
votes
9answers
180k views

How to deal with perfect separation in logistic regression?

If you have a variable which perfectly separates zeroes and ones in target variable, R will yield the following "perfect or quasi perfect separation" warning message: ...
334
votes
10answers
307k views

Difference between logit and probit models

What is the difference between Logit and Probit model? I'm more interested here in knowing when to use logistic regression, and when to use Probit. If there is any literature which defines it using ...
52
votes
1answer
42k views

How to interpret type I, type II, and type III ANOVA and MANOVA?

My primary question is how to interpret the output (coefficients, F, P) when conducting a Type I (sequential) ANOVA? My specific research problem is a bit more complex, so I will break my example ...
176
votes
3answers
100k views

R's lmer cheat sheet

There's a lot of discussion going on on this forum about the proper way to specify various hierarchical models using lmer. I thought it would be great to have all ...
191
votes
4answers
307k views

How to interpret a QQ plot

I am working with a small dataset (21 observations) and have the following normal QQ plot in R: Seeing that the plot does not support normality, what could I infer about the underlying distribution? ...
261
votes
2answers
185k views

Interpretation of R's lm() output

The help pages in R assume I know what those numbers mean, but I don't. I'm trying to really intuitively understand every number here. I will just post the output and comment on what I found out. ...
114
votes
1answer
64k views

Crossed vs nested random effects: how do they differ and how are they specified correctly in lme4?

Here is how I have understood nested vs. crossed random effects: Nested random effects occur when a lower level factor appears only within a particular level of an upper level factor. For ...
42
votes
4answers
33k views

Does the sign of scores or of loadings in PCA or FA have a meaning? May I reverse the sign?

I performed principal component analysis (PCA) with R using two different functions (prcomp and princomp) and observed that the ...
134
votes
6answers
255k views

Correlations with unordered categorical variables

I have a dataframe with many observations and many variables. Some of them are categorical (unordered) and the others are numerical. I'm looking for associations between these variables. I've been ...
116
votes
2answers
56k views

Removal of statistically significant intercept term increases $R^2$ in linear model

In a simple linear model with a single explanatory variable, $\alpha_i = \beta_0 + \beta_1 \delta_i + \epsilon_i$ I find that removing the intercept term improves the fit greatly (value of $R^2$ ...
62
votes
5answers
76k views

Using principal component analysis (PCA) for feature selection

I'm new to feature selection and I was wondering how you would use PCA to perform feature selection. Does PCA compute a relative score for each input variable that you can use to filter out ...
39
votes
2answers
18k views

Simulation of logistic regression power analysis - designed experiments

This question is in response to an answer given by @Greg Snow in regards to a question I asked concerning power analysis with logistic regression and SAS ...
41
votes
1answer
40k views

Alternatives to one-way ANOVA for heteroskedastic data

I have data from 3 groups of algae biomass ($A$, $B$, $C$) which contain unequal sample sizes ($n_A=15$, $n_B=13$, $n_C=12$) and I would like compare if these groups are from the same population. One-...
57
votes
3answers
32k views

Box-Cox like transformation for independent variables?

Is there a Box-Cox like transformation for independent variables? That is, a transformation that optimizes the $x$ variable so that the y~f(x) will make a more ...
57
votes
1answer
16k views

Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what?

I'm trying to predict a binary outcome using 50 continuous explanatory variables (the range of most of the variables is $-\infty$ to $\infty$). My data set has almost 24,000 rows. When I run ...
44
votes
1answer
11k views

Why do my p-values differ between logistic regression output, chi-squared test, and the confidence interval for the OR?

I have built a logistic regression where the outcome variable is being cured after receiving treatment (Cure vs. No Cure). All ...
98
votes
1answer
77k views

Interpreting plot.lm()

I had a question about interpreting the graphs generated by plot(lm) in R. I was wondering if you guys could tell me how to interpret the scale-location and leverage-residual plots? Any comments ...
30
votes
4answers
47k views

What is the difference between McNemar's test and the chi-squared test, and how do you know when to use each?

I have tried reading up on different sources, but I am still not clear what test would be the appropriate in my case. There are three different questions I am asking about my dataset: The subjects ...
134
votes
3answers
154k views

How are the standard errors of coefficients calculated in a regression?

For my own understanding, I am interested in manually replicating the calculation of the standard errors of estimated coefficients as, for example, come with the output of the ...
65
votes
8answers
42k views

Is PCA followed by a rotation (such as varimax) still PCA?

I have tried to reproduce some research (using PCA) from SPSS in R. In my experience, principal() function from package psych ...
16
votes
2answers
2k views

What is happening here, when I use squared loss in logistic regression setting?

I am trying to use squared loss to do binary classification on a toy data set. I am using mtcars data set, use mile per gallon and weight to predict transmission ...
20
votes
3answers
7k views

Obtaining a formula for prediction limits in a linear model (i.e.: prediction intervals)

Let's take the following example: set.seed(342) x1 <- runif(100) x2 <- runif(100) y <- x1+x2 + 2*x1*x2 + rnorm(100) fit <- lm(y~x1*x2) This creates a ...
67
votes
1answer
64k views

Understanding ROC curve

I'm having trouble understanding the ROC curve. Is there any advantage / improvement in area under the ROC curve if I build different models from each unique subset of the training set and use it to ...
47
votes
1answer
36k views

Regression: Transforming Variables

When transforming variables, do you have to use all of the same transformation? For example, can I pick and choose differently transformed variables, as in: Let, $x_1,x_2,x_3$ be age, length of ...
32
votes
1answer
21k views

Comparing hierarchical clustering dendrograms obtained by different distances & methods

[The initial title "Measurement of similarity for hierarchical clustering trees" was later changed by @ttnphns to better reflect the topic] I am performing a number of hierarchical cluster analyses ...
18
votes
3answers
23k views

Continuous dependent variable with ordinal independent variable

Given a continuous dependent variable y and independent variables including an ordinal variable X1, how do I fit a linear model in R? Are there papers about this ...
24
votes
2answers
43k views

How does the inverse transform method work?

How does the inversion method work? Say I have a random sample $X_1,X_2,...,X_n$ with density $f(x;\theta)={1\over \theta} x^{(1-\theta)\over \theta}$ over $0<x<1$ and therefore with cdf $F_X(x)=...
86
votes
8answers
64k views

Generate a random variable with a defined correlation to an existing variable(s)

For a simulation study I have to generate random variables that show a predefined (population) correlation to an existing variable $Y$. I looked into the R ...
69
votes
4answers
20k views

How should tiny $p$-values be reported? (and why does R put a minimum on 2.22e-16?)

For some tests in R, there is a lower limit on the p-value calculations of $2.22 \cdot 10^{-16}$. I'm not sure why it's this number, if there is a good reason for ...
39
votes
2answers
32k views

How to find a good fit for semi-sinusoidal model in R?

I want to assume that the sea surface temperature of the Baltic Sea is the same year after year, and then describe that with a function / linear model. The idea I had was to just input year as a ...
28
votes
7answers
32k views

Testing for linear dependence among the columns of a matrix

I have a correlation matrix of security returns whose determinant is zero. (This is a bit surprising since the sample correlation matrix and the corresponding covariance matrix should theoretically be ...
27
votes
5answers
10k views

Time taken to hit a pattern of heads and tails in a series of coin-tosses

Inspired by Peter Donnelly's talk at TED, in which he discusses how long it would take for a certain pattern to appear in a series of coin tosses, I created the following script in R. Given two ...
65
votes
8answers
101k views

How to simulate data that satisfy specific constraints such as having specific mean and standard deviation?

This question is motivated by my question on meta-analysis. But I imagine that it would also be useful in teaching contexts where you want to create a dataset that exactly mirrors an existing ...
39
votes
9answers
10k views

How can I efficiently model the sum of Bernoulli random variables?

I am modeling a random variable ($Y$) which is the sum of some ~15-40k independent Bernoulli random variables ($X_i$), each with a different success probability ($p_i$). Formally, $Y=\sum X_i$ where $\...
158
votes
2answers
210k views

How to determine which distribution fits my data best?

I have a dataset and would like to figure out which distribution fits my data best. I used the fitdistr() function to estimate the necessary parameters to ...
30
votes
3answers
40k views

Computing p-value using bootstrap with R

I use "boot" package to compute an approximated 2-sided bootstrapped p-value but the result is too far away from p-value of using t.test. I can't figure out what I did wrong in my R code. Can someone ...
24
votes
2answers
19k views

Why do lme and aov return different results for repeated measures ANOVA in R?

I am trying to move from using the ez package to lme for repeated measures ANOVA (as I hope I will be able to use custom ...
21
votes
2answers
49k views

Significance of categorical predictor in logistic regression

I am having trouble interpreting the z values for categorical variables in logistic regression. In the example below I have a categorical variable with 3 classes and according to the z value, CLASS2 ...
33
votes
2answers
50k views

Interpretation of plot (glm.model)

Can anyone tell me how to interpret the 'residuals vs fitted', 'normal q-q', 'scale-location', and 'residuals vs leverage' plots? I am fitting a binomial GLM, saving it and then plotting it.
39
votes
4answers
13k views

Good methods for density plots of non-negative variables in R?

plot(density(rexp(100)) Obviously all density to the left of zero represents bias. I'm looking to summarize some data for non-statisticians, and I want to avoid ...
27
votes
3answers
42k views

Why is nls() giving me “singular gradient matrix at initial parameter estimates” errors?

I have some basic data on emission reductions and cost per car: ...
69
votes
9answers
151k views

How to obtain the p-value (check significance) of an effect in a lme4 mixed model?

I use lme4 in R to fit the mixed model lmer(value~status+(1|experiment))) where value is continuous, status and experiment are factors, and I get ...
69
votes
4answers
18k views

Why does including latitude and longitude in a GAM account for spatial autocorrelation?

I have produced generalized additive models for deforestation. To account for spatial-autocorrelation, I have included latitude and longitude as a smoothed, interaction term (i.e. s(x,y)). I've based ...
74
votes
1answer
79k views

How to interpret coefficients in a Poisson regression?

How can I interpret the main effects (coefficients for dummy-coded factor) in a Poisson regression? Assume the following example: ...
51
votes
4answers
105k views

How to statistically compare two time series?

I have two time series, shown in the plot below: The plot is showing the full detail of both time series, but I can easily reduce it to just the coincident observations if needed. My question is: ...
29
votes
3answers
26k views

How to perform orthogonal regression (total least squares) via PCA?

I always use lm() in R to perform linear regression of $y$ on $x$. That function returns a coefficient $\beta$ such that $$y = \beta x.$$ Today I learned about ...
20
votes
3answers
6k views

I'm getting “jumpy” loadings in rollapply PCA in R. Can I fix it?

I have 10 years of daily returns data for 28 different currencies. I wish to extract the first principal component, but rather than operate PCA on the whole 10 years, I want to rollapply a 2 year ...
19
votes
3answers
17k views

Comparing non nested models with AIC

Say we have to GLMMs mod1 <- glmer(y ~ x + A + (1|g), data = dat) mod2 <- glmer(y ~ x + B + (1|g), data = dat) These models are not nested in the usual ...
26
votes
3answers
23k views

Interpreting plot of residuals vs. fitted values from Poisson regression

I am trying to fit data with a GLM (poisson regression) in R. When I plotted the residuals vs the fitted values, the plot created multiple (almost linear with a slight concave curve) "lines". What ...
14
votes
2answers
4k views

Biased bootstrap: is it okay to center the CI around the observed statistic?

This is similar to Bootstrap: estimate is outside of confidence interval I have some data that represents counts of genotypes in a population. I want to estimate genetic diversity using Shannon's ...

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