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`.
4,149
questions
203
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10
answers
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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:
...
- 6,981
381
votes
12
answers
367k
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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 ...
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218
votes
3
answers
158k
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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 ...
70
votes
2
answers
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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 ...
- 1,881
235
votes
4
answers
449k
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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? ...
- 19.2k
60
votes
4
answers
37k
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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 ...
- 20.6k
52
votes
4
answers
49k
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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 ...
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139
votes
3
answers
79k
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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 $R^2$ ...
- 2,212
277
votes
2
answers
225k
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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. ...
- 4,241
147
votes
6
answers
287k
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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 ...
- 1,767
52
votes
1
answer
49k
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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-...
- 521
43
votes
2
answers
24k
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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 ...
- 7,940
63
votes
1
answer
20k
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Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what? [duplicate]
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 ...
- 763
54
votes
1
answer
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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 ...
- 740
102
votes
8
answers
83k
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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 ...
- 4,550
101
votes
1
answer
87k
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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 ...
- 1,011
40
votes
4
answers
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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 ...
- 733
36
votes
3
answers
21k
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How to perform isometric log-ratio transformation
I have data on movement behaviours (time spent sleeping, sedentary, and doing physical activity) that sums to approximately 24 (as in hours per day). I want to create a variable that captures the ...
- 363
51
votes
1
answer
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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 ...
- 6,872
23
votes
2
answers
6k
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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 ...
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26
votes
2
answers
62k
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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)=...
- 1,223
162
votes
3
answers
195k
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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 ...
- 1,723
76
votes
4
answers
27k
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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 ...
- 1,362
80
votes
1
answer
75k
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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 ...
- 1,005
70
votes
8
answers
56k
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 ...
- 3,368
41
votes
2
answers
39k
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 ...
- 513
22
votes
3
answers
10k
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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 ...
- 20.6k
35
votes
1
answer
28k
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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 ...
- 2,132
23
votes
3
answers
23k
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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 ...
- 1,615
22
votes
3
answers
30k
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 ...
- 2,021
30
votes
5
answers
12k
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 ...
- 403
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votes
11
answers
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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
...
- 2,071
41
votes
9
answers
13k
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 $\...
- 1,271
31
votes
7
answers
39k
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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 ...
- 3,051
72
votes
8
answers
118k
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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 ...
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votes
3
answers
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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 ...
- 2,767
21
votes
3
answers
7k
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 ...
- 1,029
114
votes
4
answers
213k
views
What is rank deficiency, and how to deal with it?
Fitting a logistic regression using lme4 ends with
Error in mer_finalize(ans) : Downdated X'X is not positive definite.
A likely cause of this error is ...
- 4,732
56
votes
2
answers
57k
views
How to simulate artificial data for logistic regression?
I know I'm missing something in my understanding of logistic regression, and would really appreciate any help.
As far as I understand it, the logistic regression assumes that the probability of a '1' ...
- 757
17
votes
2
answers
6k
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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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195
votes
3
answers
275k
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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 ...
- 2,055
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votes
4
answers
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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 ...
- 953
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votes
6
answers
177k
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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: ...
- 2,087
41
votes
2
answers
68k
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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.
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96
votes
7
answers
168k
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Calculating the parameters of a Beta distribution using the mean and variance
How can I calculate the $\alpha$ and $\beta$ parameters for a Beta distribution if I know the mean and variance that I want the distribution to have? Examples of an R command to do this would be most ...
- 1,588
26
votes
2
answers
55k
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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 ...
- 1,491
37
votes
4
answers
21k
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Why does logistic regression become unstable when classes are well-separated?
Why is it that logistic regression becomes unstable when classes are well-separated? What does well-separated classes mean? I would really appreciate if someone can explain with an example.
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votes
3
answers
59k
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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:
...
- 431
22
votes
1
answer
22k
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What is the difference between logistic regression and Fractional response regression?
As far as I know, the difference between logistic model and fractional response model (frm) is that the dependent variable (Y) in which frm is [0,1], but logistic is {0, 1}. Further, frm uses the ...
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votes
3
answers
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Can the scaling values in a linear discriminant analysis (LDA) be used to plot explanatory variables on the linear discriminants?
Using a biplot of values obtained through principal component analysis, it is possible to explore the explanatory variables that make up each principle component. Is this also possible with Linear ...
- 1,683