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3815 | 2 | null | 3814 | 41 | null | Irene Stratton and colleague published a short paper about a closely related question:
Stratton IM, Neil A. [How to ensure your paper is rejected by the statistical reviewer](https://onlinelibrary.wiley.com/doi/full/10.1111/j.1464-5491.2004.01443.x). Diabetic Medicine 2005; 22(4):371-373.
| null | CC BY-SA 4.0 | null | 2010-10-20T19:13:42.330 | 2019-06-25T12:56:38.810 | 2019-06-25T12:56:38.810 | 173082 | 449 | null |
3816 | 2 | null | 3814 | 73 | null | What particularly irritates me personally is people who clearly used user-written packages for statistical software but don't cite them properly, or at all, thereby failing to give any credit to the authors. Doing so is particularly important when the authors are in academia and their jobs depend on publishing papers t... | null | CC BY-SA 2.5 | null | 2010-10-20T19:28:41.487 | 2010-10-20T19:28:41.487 | null | null | 449 | null |
3817 | 2 | null | 3814 | 70 | null | Goodness me, so many things come to mind...
- Stepwise regression
- Splitting continuous data into
groups
- Giving p-values but no measure of
effect size
- Describing data using the mean and
the standard deviation without
indicating whether the data were
more-or-less symmetric and unimodal
- Figures without clear ... | null | CC BY-SA 2.5 | null | 2010-10-20T19:29:29.613 | 2010-10-20T19:29:29.613 | null | null | 1352 | null |
3818 | 1 | null | null | 1 | 3666 | I have three variables,
1. Irrational Beliefs (Categorical)
2. Anxiety State/ Trait (Categorical)
3. Personality Traits (Categorical)
Which statistical analyses can be used?
| Analysis with three categorical variables | CC BY-SA 2.5 | null | 2010-10-20T19:37:42.267 | 2010-10-21T07:23:20.837 | 2010-10-20T20:18:42.270 | null | 1649 | [
"categorical-data"
] |
3819 | 2 | null | 3814 | 32 | null | The code used to generate the simulated results is not provided. After asking for the code, it demands additional work to get it to run on a referee generated dataset.
| null | CC BY-SA 2.5 | null | 2010-10-20T19:41:32.543 | 2010-10-21T15:43:30.690 | 2010-10-21T15:43:30.690 | 8 | 603 | null |
3820 | 1 | 3825 | null | 7 | 6562 | I've been asked a question - if I calculate some sd, can I change one value and still keep the same sd.
The answer is simply yes. For example:
```
sd(c(2,3,4))
sd(c(3,4,5))
```
But what I wondered then is, assuming you change k values, under what rules do you change them so to always keep the same sd (is it true to ... | When does the sd stay the same, even after values in the sample were changed? | CC BY-SA 2.5 | null | 2010-10-20T19:43:42.297 | 2014-03-11T17:29:55.577 | 2010-10-20T20:56:22.620 | 919 | 253 | [
"standard-deviation"
] |
3821 | 2 | null | 3820 | 2 | null | Suppose that you have a random variable $X$ and you wish to find the set of transformations $Y=f(X)$ such that the standard deviation of $Y$ is the identical to the standard deviation of $X$.
Consider first the set of linear transformations:
$Y = a X + b$ where $a, b$ are constants.
It is clear that:
$Var(Y) = a^2 Var(... | null | CC BY-SA 2.5 | null | 2010-10-20T19:48:29.650 | 2010-10-20T20:15:24.157 | 2010-10-20T20:15:24.157 | null | null | null |
3822 | 1 | null | null | 4 | 432 | I have 6 similarity matrices reflecting the proximity of 100 pairs of sounds. Similarity indices are in the range [0,1], with higher values indicating sounds perceived as more alike. What is the most appropriate metric I can use to estimate the inter-rater reliability between them?
Thanks a lot.
| Inter-rater reliability between similarity matrices | CC BY-SA 2.5 | null | 2010-10-20T19:57:52.263 | 2010-10-22T07:59:16.753 | 2010-10-20T20:09:39.270 | 930 | 1564 | [
"reliability",
"agreement-statistics"
] |
3823 | 2 | null | 3814 | 31 | null | Plagiarism (theoretical or methodological). My first review was indeed for a paper figuring many unreferenced copy/paste from a well-established methodological paper published 10 years ago.
Just found a couple of interesting papers on this topic: [Authorship and plagiarism in science](http://wrt-howard.syr.edu/Bibs/Pla... | null | CC BY-SA 2.5 | null | 2010-10-20T20:23:38.740 | 2010-10-21T06:27:00.043 | 2010-10-21T06:27:00.043 | 930 | 930 | null |
3824 | 2 | null | 3814 | 26 | null | When we ask the authors for
- minor comment about an idea we have (in this sense, this not considered as a reason for rejecting the paper but just to be sure the authors are able to discuss another POV), or
- unclear or contradicting results,
and that authors don't really answer in case (1) or that the incriminat... | null | CC BY-SA 2.5 | null | 2010-10-20T20:29:24.090 | 2010-10-20T20:29:24.090 | null | null | 930 | null |
3825 | 2 | null | 3820 | 7 | null | The question is about the data, not random variables.
Let $X = (x_1, x_2, \ldots, x_n)$ be the data and $Y = (y_1, y_2, \ldots, y_n)$ be additive changes to the data so that the new values are $(x_1+y_1, \ldots, x_n+y_n)$. From
$$\text{Var}(X) = \text{Var}(X+Y) = \text{Var}(X) + 2 \text{Cov}(X,Y) + \text{Var}(Y)$$
we ... | null | CC BY-SA 3.0 | null | 2010-10-20T20:47:18.890 | 2014-03-11T17:29:55.577 | 2014-03-11T17:29:55.577 | 919 | 919 | null |
3826 | 1 | 3877 | null | 4 | 6550 | How does one calculate Cohen's d and confidence intervals after logit in Stata?
| How does one calculate Cohen's d and confidence intervals after logit in Stata? | CC BY-SA 2.5 | null | 2010-10-20T20:51:59.437 | 2010-10-22T07:24:42.113 | null | null | null | [
"confidence-interval",
"stata",
"effect-size",
"cohens-d"
] |
3827 | 2 | null | 3826 | 8 | null | Cohen’s d is not directly available in Stata, and you have to resort on external macros, e.g. [sizefx](http://econpapers.repec.org/software/bocbocode/s456738.htm) (`ssc install sizefx`). It works fine if you have to series of values, but I found it less handy when you work with a full data set because there's no possib... | null | CC BY-SA 2.5 | null | 2010-10-20T21:02:48.473 | 2010-10-21T09:57:00.433 | 2010-10-21T09:57:00.433 | 930 | 930 | null |
3828 | 2 | null | 3818 | 2 | null | If you're after a general way to model multiway [contingency tables](http://en.wikipedia.org/wiki/Contingency_table), one powerful approach is to use [Poisson regression](http://en.wikipedia.org/wiki/Poisson_regression), often called a log-linear model in this context.
A classic paper on this is [Nelder (1974)](http:/... | null | CC BY-SA 2.5 | null | 2010-10-20T21:46:53.727 | 2010-10-20T21:46:53.727 | null | null | 449 | null |
3829 | 2 | null | 3814 | 19 | null | When they don't sufficiently explain their analysis and/or include simple errors that make it difficult to work out what actually was done. This often includes throwing around a lot of jargon, by way of explanation, which is more ambiguous than the author seems to realize and also may be misused.
| null | CC BY-SA 2.5 | null | 2010-10-20T22:55:12.767 | 2010-10-20T22:55:12.767 | null | null | null | null |
3831 | 2 | null | 3788 | 2 | null | Whether a set of observations are iid or not is a decision that is typically taken after a consideration of the underlying data generating process. In your case, the underlying data generating process seems to be the measurements of the speed of a river. I would not consider these observations to be independent. If a p... | null | CC BY-SA 2.5 | null | 2010-10-21T00:47:55.787 | 2010-10-21T00:53:22.890 | 2010-10-21T00:53:22.890 | null | null | null |
3832 | 2 | null | 3804 | 2 | null | Lets see if I understand Harlan's (and Srikant's) formulation correctly.
$$\pi_1 \sim beta(\alpha_1,\beta_1)$$
$$\pi_2 \sim beta(\alpha_2,\beta_2)$$
Say, $\pi_1$ corresponds to the set of data for which you have less information apriori and $\pi_2$ is for the more precise data set.
Using Srikant's formulation:
$$\pi(p)... | null | CC BY-SA 2.5 | null | 2010-10-21T04:34:05.837 | 2010-10-21T05:51:11.413 | 2010-10-21T05:51:11.413 | 1307 | 1307 | null |
3833 | 2 | null | 3818 | 4 | null | @onestop is literally correct. If you have three unordered categorical variables, techniques like loglinear modelling are appropriate.
@Neelam However, I doubt that your data is unordered categorical.
From my experience with measures of psychological scales measuring irrational beliefs, anxiety states and traits, and p... | null | CC BY-SA 2.5 | null | 2010-10-21T06:43:36.237 | 2010-10-21T07:23:20.837 | 2017-04-13T12:44:46.680 | -1 | 183 | null |
3834 | 2 | null | 3822 | 3 | null | My first idea would be to try some kind of cluster analysis (e.g. [hierarchical clustering](http://en.wikipedia.org/wiki/Hierarchical_clustering)) on each similarity matrix, and compare the classification trees across raters. We can derive a similarity index from all dendrograms, as discussed here, [A measure to descri... | null | CC BY-SA 2.5 | null | 2010-10-21T07:22:40.340 | 2010-10-22T07:59:16.753 | 2017-04-13T12:44:53.777 | -1 | 930 | null |
3835 | 1 | 3846 | null | 4 | 104 | This example was taken from Mathematical Statistics : A Unified Introduction (ISBN 9780387227696), page 58, under the section 'The Principle of Least Squares'. I think my problem has more to do with algebra but since this is a statistics book, I thought I should post here...
Anyway, I need to estimate k base on this eq... | Estimating k in d=kv | CC BY-SA 2.5 | null | 2010-10-21T07:58:40.967 | 2010-10-22T01:18:58.907 | null | null | 1636 | [
"least-squares"
] |
3837 | 2 | null | 3051 | 4 | null | ```
library(zoo)
x=c(4, 5, 7, 3, 9, 8)
rollmean(x,3)
```
or
```
library(TTR)
x=c(4, 5, 7, 3, 9, 8)
SMA(x,3)
```
| null | CC BY-SA 2.5 | null | 2010-10-21T09:17:02.463 | 2010-10-21T09:17:02.463 | null | null | 1709 | null |
3840 | 1 | null | null | 6 | 1198 | I have two time series, series1 and series2. My aim is to find how much Series2 is different from Series1, automatically/quantitatively.
Image can be seen in its original size by [clicking here](http://img713.imageshack.us/img713/3401/image001eg.gif).
Series1 is the expe... | Automatic test measuring dissimilarity between two time series | CC BY-SA 2.5 | null | 2010-10-21T10:49:45.380 | 2010-10-21T14:06:00.943 | 2010-10-21T11:20:27.300 | 1352 | 1655 | [
"distributions",
"time-series",
"computational-statistics",
"cross-correlation",
"kolmogorov-smirnov-test"
] |
3841 | 1 | 3866 | null | 11 | 186 | I have two years of data which looks basically like this:
Date ___ Violence Y/N? _ Number of patients
1/1/2008 ____ 0 __________ 11
2/1/2008 ____ 0 _________ 11
3/1/2008 _____1 __________ 12
4/1/2008 _____0 __________ 12
...
31/12/2009____ 0__________ 14
i.e. two years of obse... | Two years of data describing occurence of violence- testing association with number of patients on ward | CC BY-SA 2.5 | null | 2010-10-21T11:07:03.723 | 2010-10-21T19:22:27.857 | null | null | 199 | [
"r",
"mixed-model",
"autocorrelation",
"panel-data"
] |
3842 | 1 | 3843 | null | 9 | 105155 | I want to create a bardiagram for these data in R (read from a CVS file):
Experiment_Name MetricA MetricB
Just_X 2 10
Just_X_and_Y 3 20
to have the following diagram:
I am beginner and I do not know even how to start.
| How to create a barplot diagram where bars are side-by-side in R | CC BY-SA 2.5 | null | 2010-10-21T11:13:44.080 | 2015-02-01T03:27:55.130 | 2010-10-21T11:18:38.177 | 1352 | 1389 | [
"r",
"data-visualization",
"barplot"
] |
3843 | 2 | null | 3842 | 13 | null | I shall assume that you are able to import your data in R with `read.table()` or the short-hand `read.csv()` functions. Then you can apply any summary functions you want, for instance `table` or `mean`, as below:
```
x <- replicate(4, rnorm(100))
apply(x, 2, mean)
```
or
```
x <- replicate(2, sample(letters[1:2], 100,... | null | CC BY-SA 2.5 | null | 2010-10-21T11:44:58.290 | 2010-10-21T11:56:50.343 | 2010-10-21T11:56:50.343 | 930 | 930 | null |
3844 | 2 | null | 1053 | 2 | null | I found "Analysis of survival data" by Cox and Oakes (Chapman and Hall Monographs on Statistics and Applied Probability - vol. 21) to be very readable and informative. No material on survival analysis in R though.
| null | CC BY-SA 2.5 | null | 2010-10-21T12:17:31.507 | 2010-10-21T12:17:31.507 | null | null | 887 | null |
3845 | 1 | 5257 | null | 6 | 2133 | Please see [question](https://stats.stackexchange.com/questions/3708/forecasting-unemployment-rate) for the background.
Following the advice of @kwak and @Andy W, I have decided to use the package plm in `R` to fit my model. Here an excerpt of the data `df` (the numbers are made up, not real data!):
reg year ... | Forecasting unemployment rate with plm | CC BY-SA 2.5 | null | 2010-10-21T12:32:34.307 | 2013-01-31T19:47:46.013 | 2020-06-11T14:32:37.003 | -1 | 1443 | [
"r",
"panel-data",
"generalized-moments"
] |
3846 | 2 | null | 3835 | 1 | null | There is a constraint imposed a few lines above the highlighted text which states:
$\sum_i{v_i (d_i-k v_i)} = 0$
Does the that help?
Edit
In response to your second comment:
Consider: $\sum_i{(d_i - l v_i)^2}$. This can be re-written as:
$\sum_i{((d_i - k v_i) + (k v_i - l v_i))^2}$
Expanding the square, we have:
$\sum... | null | CC BY-SA 2.5 | null | 2010-10-21T12:33:03.850 | 2010-10-22T01:18:58.907 | 2010-10-22T01:18:58.907 | null | null | null |
3847 | 2 | null | 3842 | 13 | null | Here ggplot version:
```
library(ggplot2)
df = melt(data.frame(A=c(2, 10), B=c(3, 20),
experiment=c("X", "X & Y")),
variable_name="metric")
ggplot(df, aes(experiment, value, fill=metric)) +
geom_bar(position="dodge")
```
| null | CC BY-SA 2.5 | null | 2010-10-21T12:58:47.983 | 2010-10-22T10:16:06.170 | 2010-10-22T10:16:06.170 | 8 | 1443 | null |
3848 | 2 | null | 3840 | 3 | null | There are many different distance measures. For starters, there's always the correlation.
You can look at the [mean square error](http://en.wikipedia.org/wiki/Mean_squared_error). In R, you can see the algorithm for time series in Rob Hyndman's [ftsa](http://cran.us.r-project.org/web/packages/ftsa/) package (see th... | null | CC BY-SA 2.5 | null | 2010-10-21T13:21:24.800 | 2010-10-21T14:06:00.943 | 2010-10-21T14:06:00.943 | 5 | 5 | null |
3849 | 1 | 5429 | null | 3 | 2136 | Are there any tools that can format and write to external file output of principal component analysis in Stata?
I'm thinking about something that will work in similar vein to [excellent] family of [estout](http://repec.org/bocode/e/estout/index.html) commands.
| How can I format and export PCA output in Stata? | CC BY-SA 2.5 | null | 2010-10-21T13:38:32.160 | 2010-12-13T12:09:19.943 | null | null | 22 | [
"pca",
"stata"
] |
3850 | 2 | null | 1053 | 4 | null | David Collett. Modelling Survival Data in Medical Research, Second Edition. Chapman & Hall/CRC. 2003. [ISBN 978-1584883258](http://en.wikipedia.org/wiki/Special%3aBookSources/9781584883258)
Software section focuses on SAS not R though.
| null | CC BY-SA 2.5 | null | 2010-10-21T14:42:28.390 | 2010-10-21T14:42:28.390 | null | null | 449 | null |
3853 | 1 | 3854 | null | 7 | 107634 | I have the following R code for creating barplot:
```
# ... here I read cvs file
mx <- rbind(results$"AVG.P10.")
colnames(mx) <- results$"RUN"
rownames(mx) <- "AVG P"
postscript(file="avg_p_result.ps")
barplot(mx, beside=T, col=c("grey"), names.arg= results$"RUN",
cex.axis = 1.5, cex.lab=1.5)
... | How to increase size of label fonts in barplot | CC BY-SA 2.5 | null | 2010-10-21T15:01:50.123 | 2010-10-21T16:21:07.947 | 2010-10-21T16:20:10.117 | 930 | 1389 | [
"r",
"boxplot"
] |
3854 | 2 | null | 3853 | 10 | null | According to `?barplot`, you need to use `cex.names=1.5`.
```
barplot(mx, beside=TRUE, col=c("grey"), names.arg=results$"RUN",
cex.axis=1.5, cex.names=1.5)
```
| null | CC BY-SA 2.5 | null | 2010-10-21T15:15:49.950 | 2010-10-21T16:21:07.947 | 2010-10-21T16:21:07.947 | 930 | 1657 | null |
3855 | 1 | 3861 | null | 6 | 998 | Imagine I have a test for a disease that returns either a positive or a negative result. I administer the test to one group twice in a single session; in another group, I administer it twice with two weeks separating the tests. The hypothesis is that the tests taken at the same time will be more consistent with each ... | Comparing test-retest reliabilities | CC BY-SA 2.5 | null | 2010-10-21T15:48:52.837 | 2010-10-21T17:14:20.710 | null | null | 71 | [
"reliability"
] |
3856 | 1 | 3865 | null | 6 | 1513 | Are there standard ways of analyzing and generating "clumpy" distributions?
- analyze: how clumpy is a given point cloud (in 1d, 2d, nd),
what are its clumpy coefficients?
- generate or synthesize a pseudo-random cloud with coefficients C
(These are the basics for any family of distributions, e.g. normal.)
There ar... | Analyze and generate "clumpy" distributions? | CC BY-SA 2.5 | null | 2010-10-21T16:20:09.727 | 2011-08-26T17:19:23.190 | 2010-10-22T13:32:28.723 | 557 | 557 | [
"clustering",
"spatial",
"autocorrelation"
] |
3857 | 1 | 3863 | null | 43 | 876 | [My workplace](http://www.hsl.gov.uk/) has employees from a very wide range of disciplines, so we generate data in lots of different forms. Consequently, each team has developed its own system for storing data. Some use Access or SQL databases; some teams (to my horror) are reliant almost entirely on Excel spreadshee... | How do I get people to take better care of data? | CC BY-SA 2.5 | null | 2010-10-21T16:26:22.880 | 2013-09-04T01:59:52.387 | 2011-10-07T02:13:18.347 | 183 | 478 | [
"dataset",
"reproducible-research",
"quality-control"
] |
3858 | 2 | null | 3855 | 1 | null | Perhaps, computing the tetrachoric correlation would be useful. See this url: [Introduction to the Tetrachoric and Polychoric Correlation Coefficients](http://www.john-uebersax.com/stat/tetra.htm)
| null | CC BY-SA 2.5 | null | 2010-10-21T16:28:13.923 | 2010-10-21T16:28:13.923 | null | null | null | null |
3859 | 2 | null | 3856 | 4 | null | I think suitable 'clumpy coefficients' are measures of spatial autocorrelation such as [Moran's I](http://en.wikipedia.org/wiki/Moran%27s_I) and [Geary's C](http://en.wikipedia.org/wiki/Geary%27s_C). Spatial statistics is not my area and I don't know about simulation though.
| null | CC BY-SA 2.5 | null | 2010-10-21T16:36:55.843 | 2010-10-21T16:36:55.843 | null | null | 449 | null |
3860 | 2 | null | 3856 | 4 | null | You could calculate an [index of dispersion](http://www.passagesoftware.net/webhelp/Dispersion_Indices.htm) measure over your space to gauge clumpiness. One starting point for more information would be the ecology packages and literature to see how they simulate such things.
| null | CC BY-SA 2.5 | null | 2010-10-21T16:36:59.993 | 2010-10-21T16:36:59.993 | null | null | 251 | null |
3861 | 2 | null | 3855 | 7 | null | Both situations are specific cases of test-retest, except that the recall period is null in the first case you described. I would also expect a larger agreement in the former case, but that may be confounded with a learning or memory effect. A chance-corrected measure of agreement, like [Cohen's kappa](http://en.wikipe... | null | CC BY-SA 2.5 | null | 2010-10-21T17:14:20.710 | 2010-10-21T17:14:20.710 | null | null | 930 | null |
3862 | 2 | null | 3857 | 12 | null | One free online resource is the set of [Statistical Good Practice Guidelines](http://www.ilri.org/biometrics/GoodStatisticalPractice/publications/guides.html) from the [Statistical Services Centre at the University of Reading](http://www.ssc.rdg.ac.uk/).
In particular:
- Data Management Guidelines for Experimental Pro... | null | CC BY-SA 3.0 | null | 2010-10-21T17:34:29.003 | 2011-10-06T22:23:20.723 | 2011-10-06T22:23:20.723 | 4756 | 449 | null |
3863 | 2 | null | 3857 | 16 | null | It's worth considering ideas from the software world. In particular you might think of setting up: a [version control repository](http://en.wikipedia.org/wiki/Revision_control) and a central database server.
Version control probably helps you out with otherwise free floating files, such as Excel and text files, etc.... | null | CC BY-SA 2.5 | null | 2010-10-21T17:45:14.913 | 2010-10-21T17:45:14.913 | null | null | 251 | null |
3864 | 2 | null | 3857 | 6 | null | I think first of all you have to ask yourself: why do people use Excel to do tasks Excel was not made for?
1) They already know how to use it
2) It works. Maybe in a clumsy way but it works and that's what they want
I copy a series of numbers in, press a button and I have a plot. As easy as that.
So, make them understa... | null | CC BY-SA 2.5 | null | 2010-10-21T17:55:24.157 | 2010-10-21T17:55:24.157 | null | null | 582 | null |
3865 | 2 | null | 3856 | 5 | null | If assessing spatial auto-correlation is what your interested in, here is a paper that simulates data and evaluates different auto-regressive models in R.
[Spatial autocorrelation and the selection of simultaneous autoregressive models](http://dx.doi.org/10.1111/j.1466-8238.2007.00334.x)
by: W. D. Kissling, G. Carl
Glo... | null | CC BY-SA 3.0 | null | 2010-10-21T18:58:11.697 | 2011-08-26T17:19:23.190 | 2011-08-26T17:19:23.190 | 1036 | 1036 | null |
3866 | 2 | null | 3841 | 2 | null | Here is an idea that connects your binary dependent variable to a continuous, unobserved variable; a connection that may let you leverage the power of time series models for continuous variables.
Define:
$V_{w,t} = 1$ if violent incident happened in ward $w$ during time period $t$ and 0 otherwise
$P_{w,t}$ : Propensit... | null | CC BY-SA 2.5 | null | 2010-10-21T19:22:27.857 | 2010-10-21T19:22:27.857 | null | null | null | null |
3867 | 2 | null | 1053 | 4 | null | Take a look at the course page for [Sociology 761: Statistical Applications in Social Research](http://socserv.socsci.mcmaster.ca/jfox/Courses/soc761/index.html). Professor [John Fox](http://socserv.socsci.mcmaster.ca/jfox/) at McMaster University has [course notes on survival analysis](http://socserv.socsci.mcmaster.c... | null | CC BY-SA 2.5 | null | 2010-10-21T20:35:15.033 | 2010-10-21T20:35:15.033 | null | null | null | null |
3868 | 1 | null | null | 5 | 606 | The nonlinear model I am fitting gamma distribution with inverse or log is not converging. There is one observation having zero value in the response variable. Does this zero affects to model the data? Any answer warmly appreciated!
| Undefined link function in gamma distribution | CC BY-SA 3.0 | 0 | 2010-10-21T23:47:03.803 | 2013-02-11T08:13:51.703 | 2013-02-11T08:13:51.703 | 19879 | null | [
"generalized-linear-model",
"fitting",
"link-function"
] |
3869 | 1 | 3871 | null | 4 | 513 | I know that if events $A$ and $B$ are independent, then $P(A\cap B) = P(A).P(B)$.
Lets say I roll a die, and define the following events:
$x$ = Number is a multiple of $3 = \lbrace 3, 6\rbrace$
$y$ = Number is more than $3 = \lbrace 4, 5, 6\rbrace$
$z$ = Number is even = $\lbrace 2, 4, 6 \rbrace$
Therefore,
$P(x) * P... | What are independent events? | CC BY-SA 4.0 | null | 2010-10-22T01:02:20.173 | 2022-07-09T18:12:00.490 | 2022-07-09T18:12:00.490 | 44269 | 1636 | [
"probability",
"independence"
] |
3870 | 2 | null | 3869 | 4 | null | I find it easiest to think of independence in terms of conditional probabilities: $X$ and $Y$ are independent if $P(Y|X)=P(Y)$ and $P(X|Y)=P(X)$. That is knowing one does not change the probability of the other. In this example,
\begin{aligned}
P(Y|X) &= P(Y \cap X) / P(X) = 1/2 = P(Y)\\
P(Y|Z) &= P(Y \cap Z) / P(Z) = ... | null | CC BY-SA 2.5 | null | 2010-10-22T01:16:57.240 | 2010-10-22T01:16:57.240 | null | null | 159 | null |
3871 | 2 | null | 3869 | 5 | null | To add to the Rob's [answer](https://stats.stackexchange.com/questions/3869/what-are-independent-events/3870#3870) the joint probability of two events in the discrete case can be decomposed as follows (See the wiki's definition for the [discrete case](http://en.wikipedia.org/wiki/Joint_probability_distribution#Discrete... | null | CC BY-SA 2.5 | null | 2010-10-22T01:33:49.437 | 2010-10-22T01:33:49.437 | 2017-04-13T12:44:20.903 | -1 | null | null |
3872 | 1 | null | null | 5 | 34780 | What statistical test can I use to compare two ratios from two independent samples. The ratios are after to before results. I need to compare the after/before ratios for two independent models and show whether they are have significant difference or not. Please help!
| Statistical test to compare two ratios from two independent models | CC BY-SA 2.5 | null | 2010-10-22T04:37:04.527 | 2020-04-27T01:57:37.307 | null | null | null | [
"statistical-significance"
] |
3873 | 2 | null | 3650 | 2 | null | So here is my motivation for the questions, although I know this is not necessary I like it when people follow up on their questions so I will do the same. I would like to thank both Srikant and whuber for their helpful answers. (I ask no-one upvote this as it is not an answer to the question and both whuber's and Srik... | null | CC BY-SA 2.5 | null | 2010-10-22T04:55:00.487 | 2010-10-22T16:38:05.127 | 2010-10-22T16:38:05.127 | 919 | 1036 | null |
3874 | 1 | 3876 | null | 17 | 17253 | I have data from patients treated with 2 different kinds of treatments during surgery.
I need to analyze its effect on heart rate.
The heart rate measurement is taken every 15 minutes.
Given that the surgery length can be different for each patient, each patient can have between 7 and 10 heart rate measurements.
So ... | Unbalanced mixed effect ANOVA for repeated measures | CC BY-SA 3.0 | null | 2010-10-22T05:03:26.650 | 2011-04-08T01:04:33.640 | 2011-04-08T01:04:33.640 | 930 | 1663 | [
"r",
"mixed-model",
"repeated-measures",
"lme4-nlme"
] |
3875 | 2 | null | 3872 | 3 | null | Any test for independence of a 2x2 contingency table will do! A chi-square or t-test are the textbook simple solutions. The "best" test in this situation is called Barnard's test for superiority -- the StatXact software will happily calculate this for you.
| null | CC BY-SA 2.5 | null | 2010-10-22T05:16:26.863 | 2010-10-22T05:16:26.863 | null | null | 1122 | null |
3876 | 2 | null | 3874 | 18 | null | The lme/lmer functions from the nlme/lme4 packages are able to deal with unbalanced designs. You should make sure that time is a numeric variable. You would also probably want to test for different types of curves as well. The code will look something like this:
```
library(lme4)
#plot data with a plot per person inclu... | null | CC BY-SA 2.5 | null | 2010-10-22T05:36:47.643 | 2010-10-28T15:44:12.870 | 2010-10-28T15:44:12.870 | 966 | 966 | null |
3877 | 2 | null | 3826 | 4 | null | Given the current issues with the user-written `sizefx` command for Stata that chl and I have uncovered, here's an alternative way of doing things in Stata using the user-written `metan` command. This is designed for meta-analysis of study-level summary data so you need to enter the means, sds and ns (which i've taken ... | null | CC BY-SA 2.5 | null | 2010-10-22T07:24:42.113 | 2010-10-22T07:24:42.113 | null | null | 449 | null |
3878 | 2 | null | 2125 | 11 | null | Correlation analysis only quantifies the relation between two variables ignoring which is dependent variable and which is independent. But before appliyng regression you have to calrify that impact of which variable you want to check on the other variable.
| null | CC BY-SA 2.5 | null | 2010-10-22T09:17:26.323 | 2010-10-22T09:51:55.363 | 2010-10-22T09:51:55.363 | null | null | null |
3879 | 1 | 3880 | null | 16 | 92346 | This question is related to [my previous question](https://stats.stackexchange.com/questions/3842/how-to-create-a-barplot-diagram-where-bars-are-side-by-side-in-r). I would like to put values over bars in barplot. I am beginner in plotting in R.
| How to put values over bars in barplot in R | CC BY-SA 2.5 | null | 2010-10-22T10:05:15.167 | 2018-01-24T13:15:14.310 | 2017-04-13T12:44:21.160 | -1 | 1389 | [
"r",
"data-visualization"
] |
3880 | 2 | null | 3879 | 16 | null | To add text to a plot, just use the `text` command. From @chl's [answer](https://stats.stackexchange.com/questions/3842/how-to-create-a-barplot-diagram-where-bars-are-side-by-side-in-r/3843#3843) to your previous question:
```
##Create data
x = replicate(2, sample(letters[1:2], 100, rep=T))
apply(x, 2, table)
##Create... | null | CC BY-SA 2.5 | null | 2010-10-22T10:10:01.447 | 2010-10-22T10:10:01.447 | 2017-04-13T12:44:21.160 | -1 | 8 | null |
3882 | 2 | null | 3879 | 3 | null | If you're learning to plot in R you might look at the [R graph gallery](https://www.r-graph-gallery.com/) (original [here](https://web.archive.org/web/20100910025837/http://addictedtor.free.fr/graphiques/)).
All the graphs there are posted with the code used to build them. Its a good resource.
| null | CC BY-SA 3.0 | null | 2010-10-22T11:20:54.903 | 2018-01-24T13:15:14.310 | 2018-01-24T13:15:14.310 | 7290 | 1475 | null |
3883 | 2 | null | 3879 | 7 | null | Another example of the use of `text` command
```
u <- c(3.2,6.6,11.7,16.3,16.6,15.4,14.6,12.7,11.4,10.2,9.8,9.1,9.1,9.0,8.8,8.4,7.7)
p <-c(3737,3761,3784,3802,3825,3839,3850,3862,3878,3890,3901,3909,3918,3926,3935,3948)
-c(385,394,401,409,422,430,434,437,437,435,436,437,439,442,447,452)
e <- c(2504,2375,2206,2071,... | null | CC BY-SA 2.5 | null | 2010-10-22T12:13:40.343 | 2010-10-22T12:13:40.343 | null | null | 339 | null |
3884 | 2 | null | 3857 | 5 | null | I underline all answers given already, but let's call a cat a cat: in many workspaces it is hardly impossible to convince management that investment in "exotic" softwaretools (exotic to them, that is) is necessary, let alone hiring somebody that could set it up and maintain it. I have told quite some clients that they ... | null | CC BY-SA 2.5 | null | 2010-10-22T12:28:30.873 | 2010-10-22T12:28:30.873 | 2020-06-11T14:32:37.003 | -1 | 1124 | null |
3885 | 1 | 3886 | null | 4 | 859 | Three unbiased estimators of standard deviation have been presented in the literature for m samples of size n. The first one is based on the sample ranges and can be obtained by
$\hat \sigma_1 = \frac{\bar R}{d_2}$
The second one is based on sample standard deviations and can be calculated by
$\hat \sigma_2 = \frac{\ba... | Computing unbiased estimators of $\sigma$ for m samples of size n | CC BY-SA 2.5 | null | 2010-10-22T13:05:30.993 | 2010-10-22T13:22:57.057 | null | null | 339 | [
"r",
"standard-deviation",
"quality-control"
] |
3886 | 2 | null | 3885 | 2 | null | Ok, I finally found them [here](http://finzi.psych.upenn.edu/R/library/IQCC/html/00Index.html)
| null | CC BY-SA 2.5 | null | 2010-10-22T13:22:57.057 | 2010-10-22T13:22:57.057 | null | null | 339 | null |
3887 | 2 | null | 3857 | 3 | null | [VisTrails: A Python-Based Scientific Workflow and Provenance System](http://us.pycon.org/2010/conference/schedule/event/13/).
This talk given at PyCon 2010 has some good ideas. Worth listening to even if you are not interested in using VisTrails or python. In the end I think if you would be able to require that there ... | null | CC BY-SA 3.0 | null | 2010-10-22T13:35:54.403 | 2013-09-04T00:37:14.277 | 2013-09-04T00:37:14.277 | 9007 | 1189 | null |
3888 | 1 | 3889 | null | 2 | 1054 | I have a series of boxplots that i am generating with ggplot2. I want to control the order in which they are displayed. Is there a way to control this order? I have two genotypes and i want them displayed as WT then KO rather than the reverse (which is what i am getting as a default). My code right now is:
```
p <-... | Reorder categorical data in ggplot2 | CC BY-SA 2.5 | null | 2010-10-22T13:58:09.980 | 2010-11-30T16:42:29.257 | 2010-11-30T16:42:29.257 | 8 | 1327 | [
"r",
"boxplot",
"ggplot2"
] |
3889 | 2 | null | 3888 | 5 | null | Would that help?
```
x <- gl(2, 20, 40, labels=c("KO","WT"))
y <- rnorm(40)
qplot(x,y)
qplot(relevel(x, "WT"),y)
```
| null | CC BY-SA 2.5 | null | 2010-10-22T14:06:48.103 | 2010-10-22T14:06:48.103 | null | null | 930 | null |
3890 | 1 | 3891 | null | 3 | 7936 | I would like to use the fuction weighted.median() in package [R.basic](http://www.stat.ucl.ac.be/ISdidactique/Rhelp/library/R.basic/html/weighted.median.html) (and some other ones too, although this one is most important).
```
install.packages("R.basic")
```
gives me:
```
package ‘R.basic’ is not available
```
and
... | package R.basic | CC BY-SA 2.5 | null | 2010-10-22T14:08:01.243 | 2014-04-23T13:54:08.877 | 2010-10-22T21:42:16.497 | 603 | 603 | [
"r"
] |
3891 | 2 | null | 3890 | 6 | null | That's because the package doesn't exist on CRAN (see [the package list](http://cran.r-project.org/web/packages/)). It may have failed a build in a recent version of R.
You can install it directly from the author's site like so:
```
install.packages(c("R.basic"), contriburl="http://www.braju.com/R/repos/")
```
See [H... | null | CC BY-SA 2.5 | null | 2010-10-22T14:12:55.267 | 2010-10-22T14:21:15.993 | 2010-10-22T14:21:15.993 | 5 | 5 | null |
3892 | 1 | 3895 | null | 11 | 4965 | Why does OLS estimation involve taking vertical deviations of the points to the line rather than horizontal distances?
| Why vertical distances? | CC BY-SA 2.5 | null | 2010-10-22T15:08:17.383 | 2019-02-19T10:51:20.247 | null | null | 333 | [
"least-squares"
] |
3893 | 1 | 4095 | null | 38 | 4205 | In all contexts I am familiar with cross-validation it is solely used with the goal of increasing predictive accuracy. Can the logic of cross validation be extended in estimating the unbiased relationships between variables?
While [this](http://dx.doi.org/10.1007/s10940-009-9077-7) paper by Richard Berk demonstrates t... | Can cross validation be used for causal inference? | CC BY-SA 2.5 | null | 2010-10-22T15:12:03.423 | 2012-05-02T18:57:33.890 | 2017-04-13T12:44:41.967 | -1 | 1036 | [
"cross-validation",
"causality"
] |
3894 | 1 | null | null | 5 | 677 | I was wondering whether it's me mis-remembering something or is there a dimensionless measure of dispersion calculated as: range/(mean or median). Where range is a difference between max and min values.
P.S. Could this be called "relative range"?
| Is there a parameter that is calculated as a range to mean ratio? | CC BY-SA 2.5 | null | 2010-10-22T15:15:30.043 | 2010-10-22T15:33:55.257 | 2010-10-22T15:24:29.867 | 219 | 219 | [
"distributions"
] |
3895 | 2 | null | 3892 | 13 | null | OLS ([ordinary least squares](http://en.wikipedia.org/wiki/Ordinary_least_squares)) assumes that the values represented by the horizontal distances are either predetermined by the experimenter or measured with high accuracy (relative to the vertical distances). When there is a question of uncertainty in the horizontal... | null | CC BY-SA 2.5 | null | 2010-10-22T15:16:37.303 | 2011-01-19T04:56:27.243 | 2011-01-19T04:56:27.243 | 919 | 919 | null |
3896 | 2 | null | 3894 | 2 | null | The [coefficient of variation](http://en.wikipedia.org/wiki/Coefficient_of_variation) is defined as (standard deviation) / mean. Is that what you're thinking of??
| null | CC BY-SA 2.5 | null | 2010-10-22T15:26:45.180 | 2010-10-22T15:26:45.180 | null | null | 449 | null |
3897 | 2 | null | 3894 | 3 | null | The measure can be seen in a few publications. I can remember a paper by Lord (1947) using the range as an approximation to the standard deviation for the t-test. So the range to mean ratio would be an approximation to the coefficient of variation which onestop has mentioned already.
| null | CC BY-SA 2.5 | null | 2010-10-22T15:33:55.257 | 2010-10-22T15:33:55.257 | null | null | 1573 | null |
3898 | 1 | null | null | 7 | 1871 | I am working with a given factor model of the form
$$y=B x +\epsilon$$
where $x$ is a random vector in $R^M$, $B$ is an $N\times M$ matrix of factor loadings, $y$ is a random vector in $R^N$ (with $N \gg M$) and $\epsilon$ is a vector of mean-zero innovations, independent of $x$. For simplicity, the innovations are no... | Factor Significance for Factor Model | CC BY-SA 2.5 | null | 2010-10-22T15:41:29.937 | 2012-09-19T06:30:07.777 | 2010-10-23T22:35:32.570 | 30 | 30 | [
"hypothesis-testing",
"factor-analysis"
] |
3899 | 2 | null | 1053 | 4 | null | I learned from Hosmer, Lemeshow & May ["Applied Survival Analysis: Regression Modeling of Time-to-Event Data"](https://rads.stackoverflow.com/amzn/click/com/0471754994) (2nd ed., 2008), which covers the basics. It also helped that I found a really cheap copy...
| null | CC BY-SA 4.0 | null | 2010-10-22T16:15:02.407 | 2022-05-10T10:07:08.253 | 2022-05-10T10:07:08.253 | 53690 | 795 | null |
3900 | 2 | null | 3898 | 1 | null | The short answer is: There is something you can do but I am not sure how meaningful it will be.
The Long answer: I will give the long answer for a simple model where we have only one unknown latent factor. The idea carries over to the more general case albeit with more complications. It follows from your factor model ... | null | CC BY-SA 2.5 | null | 2010-10-22T16:21:05.233 | 2010-10-22T16:21:05.233 | null | null | null | null |
3901 | 2 | null | 2504 | 5 | null | The counterexample is not relevant to the question asked. You want to test the null hypothesis that a sample of i.i.d. random variables is drawn from a distribution having finite variance, at a given significance level. I recommend a good reference text like "Statistical Inference" by Casella to understand the use and ... | null | CC BY-SA 2.5 | null | 2010-10-22T19:15:54.743 | 2010-10-22T19:15:54.743 | null | null | 30 | null |
3902 | 1 | 3906 | null | 1 | 1643 | Does 'corr' function in Matlab consider correction for tied ranks while calculating Spearman correlation coefficient?
Thanks.
| Does corr function in Matlab consider correction for tied ranks? | CC BY-SA 2.5 | null | 2010-10-22T19:26:11.547 | 2019-06-29T08:19:46.140 | 2019-06-29T08:19:46.140 | 3277 | 1564 | [
"correlation",
"matlab",
"ties"
] |
3903 | 2 | null | 3892 | 1 | null | Interesting Question. My answer would be that when we are fitting an OLS model we are implicitly and primarily trying to predict/explain the dependent variable at hand - the "Y" in the "Y vs X." As such, our main concern would be to minimize the distance from our fitted line to the actual observations with respect to t... | null | CC BY-SA 2.5 | null | 2010-10-22T20:36:49.587 | 2010-10-22T20:36:49.587 | null | null | 1501 | null |
3904 | 2 | null | 3734 | 168 | null | I apologize in advance for the length of this post: it is with some trepidation that I let it out in public at all, because it takes some time and attention to read through and undoubtedly has typographic errors and expository lapses. But here it is for those who are interested in the fascinating topic, offered in the... | null | CC BY-SA 4.0 | null | 2010-10-22T21:11:42.460 | 2021-03-25T13:32:15.133 | 2021-03-25T13:32:15.133 | 919 | 919 | null |
3906 | 2 | null | 3902 | 3 | null | looking in the `corr` function, I see that it calls `tiedrank`:
```
$ grep -B 1 tiedrank corr.m
case 'k' % Kendall's tau
[xrank, xadj] = tiedrank(xi,1);
[yrank, yadj] = tiedrank(yj,1);
--
case 's' % Spearman's rank correlation
[xrank, xadj] = tiedrank(xi,0);
[yrank,... | null | CC BY-SA 2.5 | null | 2010-10-23T00:16:03.480 | 2010-10-23T00:16:03.480 | null | null | 795 | null |
3907 | 1 | 4073 | null | 6 | 4375 | We have prospective data from an observational registry and wish to consider the affects of a gene on time to cardiovascular events. The data includes standard data like age, gender, ... and also the date(age) of a cardio event.
In general terms what are the conditions/assumptions/requirements of a starting time for su... | Start time requirements or assumptions for survival analysis | CC BY-SA 2.5 | null | 2010-10-23T01:00:11.397 | 2023-03-03T10:44:07.670 | 2010-10-24T16:31:20.160 | null | 1189 | [
"regression",
"survival"
] |
3909 | 2 | null | 3893 | 18 | null | This is a really interesting question and I don't offer any specific citations. However, in general, I'd say, NO, in and of itself, cross-validation does not offer any insight into causality. In absence of a designed experiment, the issue of causality is always uncertain. As you suggest, cross-validation can and wil... | null | CC BY-SA 2.5 | null | 2010-10-23T05:14:26.467 | 2010-10-24T18:29:37.743 | 2010-10-24T18:29:37.743 | 485 | 485 | null |
3910 | 2 | null | 3724 | 6 | null | Use VAR (with n-1 denominator) when you wish to estimate the variance of the underlying population from the sample, or VARP (with n denominator) when the sample is the population.
I find the name "population variance" quite ambiguous...
| null | CC BY-SA 2.5 | null | 2010-10-23T06:00:07.847 | 2010-10-23T06:00:07.847 | null | null | 1679 | null |
3911 | 1 | null | null | 33 | 3525 | If I understand correctly a confidence interval of a parameter is an interval constructed by a method which yields intervals containing the true value for a specified proportion of samples. So the 'confidence' is about the method rather than the interval I compute from a particular sample.
As a user of statistics I ha... | When are confidence intervals useful? | CC BY-SA 2.5 | null | 2010-10-23T07:48:41.417 | 2011-06-07T12:24:47.820 | 2017-04-13T12:19:38.447 | -1 | 1393 | [
"confidence-interval",
"interpretation"
] |
3912 | 2 | null | 3911 | 15 | null | I like to think of CIs as some way to escape the Hypothesis Testing (HT) framework, at least the binary decision framework following [Neyman](http://j.mp/awJEkH)'s approach, and keep in line with theory of measurement in some way. More precisely, I view them as more close to the reliability of an estimation (a differen... | null | CC BY-SA 2.5 | null | 2010-10-23T08:09:48.700 | 2010-10-23T08:17:26.293 | 2010-10-23T08:17:26.293 | 930 | 930 | null |
3913 | 2 | null | 3892 | 1 | null | It possibly also relates to designed experiments - if x is a controlled quantity that is part of the experimental design, it is treated as deterministic; whilst y is the outcome, and is a random quantity. x might be a continuous quantity (eg concentration of some drug) but could be a 0/1 split (leading to a 2 sample ... | null | CC BY-SA 2.5 | null | 2010-10-23T08:22:28.610 | 2010-10-23T08:22:28.610 | null | null | 1680 | null |
3914 | 2 | null | 3911 | 7 | null | An alternative approach relevant to your 2nd Q, "Are there ways of looking at confidence intervals, at least in some circumstances, which would be meaningful to users of statistics?":
You should take a look at [Bayesian inference](http://en.wikipedia.org/wiki/Bayesian_statistics) and the resulting [credible intervals](... | null | CC BY-SA 2.5 | null | 2010-10-23T08:45:56.277 | 2010-10-23T08:45:56.277 | null | null | 449 | null |
3915 | 1 | 3916 | null | 12 | 3647 | I am trying to assess a 20-item multliple choice test. I want to perform an item analysis such as can be found in [this example](http://www.utexas.edu/academic/ctl/assessment/iar/students/report/itemanalysis-example.php). So for each question I want the P-value and the correlation with the total, and the distribution... | Item Analysis for an R newbie | CC BY-SA 2.5 | null | 2010-10-23T11:19:34.040 | 2010-10-25T13:55:00.963 | 2010-10-25T13:55:00.963 | 930 | 1681 | [
"r",
"correlation",
"psychometrics",
"scales"
] |
3916 | 2 | null | 3915 | 11 | null | I can suggest you at least two packages that allow to perform these tasks: [psych](http://cran.r-project.org/web/packages/psych/index.html) (`score.items`) and [ltm](http://cran.r-project.org/web/packages/ltm/index.html) (`descript`). The [CTT](http://cran.r-project.org/web/packages/CTT/index.html) package seems also t... | null | CC BY-SA 2.5 | null | 2010-10-23T11:59:38.010 | 2010-10-23T19:56:24.563 | 2010-10-23T19:56:24.563 | 930 | 930 | null |
3917 | 2 | null | 3893 | 12 | null | This is a good question, but the answer is definitely no: cross-validation will not improve causal inference. If you have a mapping between symptoms and diseases, cross-validation will help to insure that your model matches their joint distribution better than if you had simply fit your model to the entire raw data set... | null | CC BY-SA 2.5 | null | 2010-10-23T12:53:21.263 | 2010-10-23T12:53:21.263 | null | null | 303 | null |
3918 | 2 | null | 3911 | 3 | null | To address your question directly: Suppose that you are contemplating the use of a machine to fill a cereal box with a certain amount of cereal. Obviously, you do not want to overfill/underfill the box. You want to assess the reliability of the machine. You perform a series of tests like so: (a) Use the machine to fill... | null | CC BY-SA 2.5 | null | 2010-10-23T13:06:45.637 | 2010-10-23T13:06:45.637 | null | null | null | null |
3919 | 2 | null | 3898 | 1 | null | Just speaking on a practical level, in my discipline (psychology) I have never seen this done for pure factor analysis.
That being said, the significance (fit really) of a statistical model is normally tested by the use of Structural Equation Modelling, where you attempt to reproduce the observed matrix of data from th... | null | CC BY-SA 2.5 | null | 2010-10-23T13:33:45.217 | 2010-10-23T13:33:45.217 | null | null | 656 | null |
3920 | 2 | null | 3915 | 8 | null | The psych package function alpha produces what you are looking for.
To export this, save the object and use the xtable function to produce LaTeX markup, which can then be formatted by any LaTeX editor.
| null | CC BY-SA 2.5 | null | 2010-10-23T13:45:54.690 | 2010-10-23T13:45:54.690 | null | null | 656 | null |
3921 | 1 | null | null | 26 | 12545 | What are good ways to visualize set of Likert responses?
For example, a set of items inquiring about the importance of X to one's decisions about A, B, C, D, E, F & G? Is there something better than stacked bar charts?
- What should be done with responses of N/A? How might they be represented?
- Should the bar charts... | Visualizing Likert Item Response Data | CC BY-SA 2.5 | null | 2010-10-23T15:04:28.670 | 2013-08-11T20:36:17.530 | 2011-03-30T18:40:07.603 | 930 | null | [
"data-visualization",
"scales",
"likert"
] |
3922 | 2 | null | 3921 | 25 | null | Stacked barcharts are generally well understood by non-statisticians, provided they are gently introduced. It is useful to scale them on a common metric (e.g. 0-100%), with a gradual color for each category if these are ordinal item (e.g. Likert). I prefer [dotchart](http://polisci.msu.edu/jacoby/research/dotplots/tpm/... | null | CC BY-SA 2.5 | null | 2010-10-23T15:11:30.267 | 2010-10-24T08:44:48.867 | 2010-10-24T08:44:48.867 | 930 | 930 | null |
3923 | 2 | null | 1576 | 13 | null | For me (and I hope this is useful) factor analysis is much more useful than PCA.
Recently, I had the pleasure of analysing a scale through factor analysis. This scale (although it's widely used in industry) was developed by using PCA, and to my knowledge had never been factor analysed.
When I performed the factor ana... | null | CC BY-SA 3.0 | null | 2010-10-23T15:11:36.053 | 2013-06-25T00:14:55.990 | 2013-06-25T00:14:55.990 | 22047 | 656 | null |
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