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4383 | 1 | 4389 | null | 11 | 3655 | [edits made in response to feedback- thanks :-) ]
Doh! More edits! Sorry!
Hello-
I am doing some rather rough and ready data collection with a survey sent out to healthcare staff using a published scale about morale and other such issues.
The only thing is that the scale is rather long with all the other things in the ... | Can one validly reduce the numbers of items in a published Likert-scale? | CC BY-SA 2.5 | null | 2010-11-10T12:32:49.143 | 2011-03-30T18:43:46.680 | 2011-03-30T18:43:46.680 | 930 | 199 | [
"psychometrics",
"scales",
"reliability",
"likert"
] |
4384 | 2 | null | 4341 | 1 | null | In Excel, a simple way to group numeric data into bins is via the Pivot Table. Pull the numeric variable into the "row labels". Now right-click on any of the values in this right column and choose "Group". You can set the min and max of the overall range and the bin size (equal bins widths for all data).
| null | CC BY-SA 2.5 | null | 2010-11-10T14:07:28.267 | 2010-11-10T14:07:28.267 | null | null | 1945 | null |
4385 | 2 | null | 4316 | 2 | null | One place where I have seen this come up is in discussions of using "intention to treat" analysis versus an analysis that tries to get at the "efficacy" of a treatment in experiments with imperfect compliance. See the Wikipedia article on "intention to treat" ([link](http://en.wikipedia.org/wiki/Intention_to_treat_anal... | null | CC BY-SA 2.5 | null | 2010-11-10T14:16:39.320 | 2010-11-10T20:24:26.790 | 2010-11-10T20:24:26.790 | 96 | 96 | null |
4386 | 2 | null | 2419 | 1 | null | I have the same issue right now: I code in Python daily, use R once in a while, and need a good boosted regression tree algorithm. While there are lots of great Python packages for advanced analytics, my searching has not found a good offering for this particular algorithm. So, the route I think I'll be taking in comin... | null | CC BY-SA 2.5 | null | 2010-11-10T14:36:25.517 | 2010-11-10T14:36:25.517 | null | null | 1080 | null |
4387 | 2 | null | 4259 | 6 | null | In Statistics, like in Data Mining, you start with data and a goal. In statistics there is a lot of focus on inference, that is, answering population-level questions using a sample. In data mining the focus is usually prediction: you create a model from your sample (training data) in order to predict test data.
The pro... | null | CC BY-SA 2.5 | null | 2010-11-10T14:38:26.370 | 2010-11-10T14:38:26.370 | null | null | 1945 | null |
4388 | 2 | null | 4337 | 2 | null | How about comparing the before and after you introduce the cash option across the two groups? Say you assign half the cinemas to the cash option (treatment) and half continue with no-cash (control). Now, you can compare how sales changed in the treatment group following the introduction of the cash option, and also com... | null | CC BY-SA 2.5 | null | 2010-11-10T14:57:03.523 | 2010-11-10T14:57:03.523 | null | null | 1945 | null |
4389 | 2 | null | 4383 | 11 | null | Although there is still some information lacking (No. individuals and items per subscale), here are some general hints about scale reduction. Also, since you are working at the questionnaire level, I don't see why its length matters so much (after all, you will just give summary statistics, like total or mean scores).
... | null | CC BY-SA 2.5 | null | 2010-11-10T15:32:50.900 | 2010-11-11T05:39:58.823 | 2017-04-13T12:44:45.783 | -1 | 930 | null |
4390 | 2 | null | 4383 | 8 | null | I guess there's no clear-cut "yes/no" answer to your question. If you arbitrarily drop items from sub-scales to create a short form of the original questionnaire, you lose the long form's psychometric validation. Things that can change are the factorial structure of the questionnaire, reliability of sub-scales, item-to... | null | CC BY-SA 2.5 | null | 2010-11-10T15:35:46.517 | 2010-11-10T16:26:03.803 | 2010-11-10T16:26:03.803 | 1909 | 1909 | null |
4391 | 2 | null | 4383 | 2 | null | One reference that you may find useful for this:
[STANTON, J. M., SINAR, E. F., BALZER, W. K. and SMITH, P. C. (2002), ISSUES AND STRATEGIES FOR REDUCING THE LENGTH OF SELF-REPORT SCALES. Personnel Psychology, 55: 167–194.](http://dx.doi.org/10.1111/j.1744-6570.2002.tb00108.x)
| null | CC BY-SA 2.5 | null | 2010-11-10T15:36:31.583 | 2010-11-10T22:49:43.327 | 2010-11-10T22:49:43.327 | 159 | 1871 | null |
4392 | 1 | 4395 | null | 1 | 2434 | Let $Z=(X+Y)/2$, where $X$ and $Y$ are independent normally-distributed random variables with known variances $\sigma^2_X$ and $\sigma^2_Y$ and unknown (and possibly different) means. Given a sample $x_1$ from $X$ and $y_1$ from $Y$, what is the maximum likelihood estimator of the mean of $Z$?
| What is the maximum likelihood estimator of the mean of two normally-distributed variables? | CC BY-SA 2.5 | null | 2010-11-10T17:13:54.410 | 2010-11-11T01:30:38.347 | 2010-11-11T01:30:38.347 | null | null | [
"estimation",
"maximum-likelihood",
"normal-distribution"
] |
4393 | 2 | null | 4347 | 4 | null | I have no experience with fuzzy things (well, apart from [Fuzzy Felt](http://en.wikipedia.org/wiki/Fuzzy_Felt)) but this book looks interesting:
Buckley, James J. Fuzzy probability and statistics. Springer, 2006. ISBN [9783540308416](http://en.wikipedia.org/w/index.php?title=Special%3ABookSources&isbn=9783540308416).
| null | CC BY-SA 2.5 | null | 2010-11-10T17:18:08.687 | 2010-11-10T17:18:08.687 | null | null | 449 | null |
4394 | 1 | null | null | 18 | 42106 | It occurred to me that, while I've pieced together some ideas over the years about the differences between statistics and biostatistics, I've never heard a formal explanation. What is the distinction between these two disciplines (currently)? And why did this distinction begin in the first place?
EDIT: I've not been ... | What is the difference between statistics and biostatistics? | CC BY-SA 2.5 | null | 2010-11-10T17:37:00.063 | 2019-06-24T14:10:12.680 | 2010-11-10T18:51:24.437 | 930 | 71 | [
"terminology",
"biostatistics"
] |
4395 | 2 | null | 4392 | 3 | null | If $Z = \frac{X+Y}{2}$ then it must be that:
$Z \sim N(\frac{\mu_X + \mu_Y}{2} , \frac{\sigma_X^2 + \sigma_Y^2}{4})$
Thus, the mle of the mean of $Z$ given that we observe $z=(x_1 + y_1)/2$ is:
$\frac{x_1 + y_1}{2}$
| null | CC BY-SA 2.5 | null | 2010-11-10T17:58:49.740 | 2010-11-10T18:16:36.003 | 2010-11-10T18:16:36.003 | null | null | null |
4396 | 1 | 4400 | null | 2 | 2952 | I have a data file in which each participant is tested many times in several blocks. The data is formatted so that each trial contains a participant id, a block number and a score. What I want to do is group the data by participant and block, then rank the scores for each group, so I can use the top 50%.
For example:
`... | In SPSS, is there any way to define a use groups of data based on combinations of variables? | CC BY-SA 2.5 | null | 2010-11-10T18:13:38.233 | 2010-12-26T13:37:32.393 | 2010-11-10T18:54:34.407 | 1950 | 1950 | [
"spss"
] |
4397 | 2 | null | 4394 | 13 | null | When I look at the Wikipedia entry for [biostatistics](http://en.wikipedia.org/wiki/Biostatistics), the relation to biometrics doesn't seem so obvious to me since, historically, biometrics was more concerned with characterizing individuals by some phenotypes of interest, with large applications in population genetics (... | null | CC BY-SA 2.5 | null | 2010-11-10T18:26:30.110 | 2010-11-10T18:48:10.007 | 2010-11-10T18:48:10.007 | 930 | 930 | null |
4398 | 2 | null | 4394 | 7 | null | To quote the "Encyclopedic dictionary of mathematics" by Kiyosi Itô (ed.):
> In many applied fields there exist systems of statistical methods which have been developed specifically for the respective fields, and although all of them are based essentially on the same general principles of statistical inference, each ha... | null | CC BY-SA 2.5 | null | 2010-11-10T18:33:59.103 | 2010-11-10T18:33:59.103 | null | null | 439 | null |
4399 | 1 | 4415 | null | 5 | 3211 | I'm looking at attempting to capture the regularity of a time series of events, one measurement per day, with a year's worth of data, and there can be at most one event a day. Say for example the day you do laundry. What I want to capture is a measurement of regularity. Capturing irregularity is straight forward: goodn... | How do I capture regularity of a time series in a normalized way? | CC BY-SA 4.0 | null | 2010-11-10T19:06:41.087 | 2022-01-11T16:51:47.820 | 2021-09-10T15:33:39.483 | 11887 | 1951 | [
"time-series",
"pattern-recognition"
] |
4400 | 2 | null | 4396 | 4 | null | Ignore my initial post and take Jon's advice, heres some sample code from the RANKS command where X1 is the variable to rank and GROUPVAR is the variable identifying groups:
```
RANK VARIABLES=X1 (A) BY GROUPVAR
/RANK
/PRINT=YES
/TIES=MEAN.
```
You can either go through the GUI to see all of its options or look ... | null | CC BY-SA 2.5 | null | 2010-11-10T19:20:20.963 | 2010-12-22T20:28:59.727 | 2010-12-22T20:28:59.727 | 1036 | 1036 | null |
4401 | 1 | null | null | 1 | 2630 | In our usage of R for a non-trivial data analysis and estimation project, we've been repeatedly burnt by how tolerant R is toward misspelled or missing columns in a data frame. Typical example is calculating the weighted mean of a variable MYVAR in a data frame using another variable WEIGHT for weights:
```
m <- weight... | Make R report error on using non-existent column name in a data frame | CC BY-SA 2.5 | null | 2010-11-10T19:25:32.353 | 2010-11-10T19:50:12.800 | 2010-11-10T19:35:48.507 | 930 | 1330 | [
"r"
] |
4402 | 2 | null | 4401 | 1 | null | Maybe, you can enclose your code into try-catch blocks, see `?try` and the associated examples. It is easy to test for the class of the results ("try-error") in turn, e.g.
```
> res <- try(log("A"), silent=TRUE)
> class(res)
[1] "try-error"
```
You can also test directly for the correct spelling, by first listing the ... | null | CC BY-SA 2.5 | null | 2010-11-10T19:35:20.923 | 2010-11-10T19:43:46.667 | 2010-11-10T19:43:46.667 | 930 | 930 | null |
4403 | 1 | null | null | 7 | 302 | We need to estimate the probability of a person getting a question right for a given content area given his history of getting questions in the same content area right in the past. We would also presumably have records on how others have done on this question and in this content area.
Is there a good way or ways of do... | Estimating the probability of a person getting a question right | CC BY-SA 2.5 | null | 2010-11-10T19:36:52.677 | 2010-11-22T22:28:42.057 | 2010-11-22T22:28:42.057 | 930 | 1618 | [
"probability",
"psychometrics",
"hypothesis-testing"
] |
4404 | 2 | null | 4401 | 3 | null | Hmm... when I tried out your example with some fake data, `weighted.mean()` actually failed:
```
#Some fake data
dat <- data.frame(x = rnorm(100), weight = rnorm(100))
#The right weight var
weighted.mean(x = dat$x, w = dat$weight)
[1] 0.6161606
#Misspelled weight var
weighted.mean(x = dat$x, w = dat$wieght)
Error in ... | null | CC BY-SA 2.5 | null | 2010-11-10T19:50:12.800 | 2010-11-10T19:50:12.800 | null | null | 71 | null |
4405 | 2 | null | 4403 | 7 | null | If I understand your question correctly, you have a set of items (pass-fail) and you want to assess the probability of endorsing the $k$th item given its preceding responses? If that's the case, what is usually done in psychometrics for educational assessment is to rely on [Item Response Model](http://en.wikipedia.org/... | null | CC BY-SA 2.5 | null | 2010-11-10T19:58:04.940 | 2010-11-10T20:05:36.893 | 2010-11-10T20:05:36.893 | 930 | 930 | null |
4406 | 2 | null | 4394 | 4 | null | Biostatistics, biometrics and biometry are synonyms. Medical statistics (sometimes called 'clinical biostatistics' for no clear reason) is a subset of these.
| null | CC BY-SA 2.5 | null | 2010-11-10T20:05:47.163 | 2010-11-10T20:05:47.163 | null | null | 449 | null |
4408 | 1 | null | null | 2 | 367 | Could anybody provide me a latest material related to Cross validation especially R package?
| Latest article or new development in cross validation? | CC BY-SA 3.0 | null | 2010-11-10T20:13:27.987 | 2022-08-09T21:01:36.430 | 2012-12-10T06:26:13.847 | 2116 | null | [
"r",
"machine-learning",
"cross-validation"
] |
4410 | 2 | null | 4408 | 7 | null | Your question is not really precise, but I think the [caret](http://caret.r-forge.r-project.org/) package and its associated vignettes may be a good start. Quoting the website, it is
>
a set of functions that attempt to
streamline the process for creating
predictive models.
In fact, it depends on a lot of other ... | null | CC BY-SA 2.5 | null | 2010-11-10T20:22:27.040 | 2010-11-10T20:22:27.040 | null | null | 930 | null |
4411 | 2 | null | 4408 | 8 | null | The following is a recent survey: "A survey of cross-validation procedures for model selection" by Sylvain Arlot and Alain Celisse (Statistics Surveys, Volume 4 (2010), 40-79.)
The full paper can be downloaded by following the PDF link on [this page](https://projecteuclid.org/journals/statistics-surveys/volume-4/issue-... | null | CC BY-SA 4.0 | null | 2010-11-10T20:51:05.220 | 2022-08-09T21:01:36.430 | 2022-08-09T21:01:36.430 | 79696 | 439 | null |
4412 | 2 | null | 1780 | 1 | null | I would recommend using Association Rule Learning for this. It allows you to find words that often co-occur.
If you have a lot of data, it will be much faster than calculating a correlation matrix.
See my video series on text mining [here](http://vancouverdata.blogspot.com/2010/11/text-analytics-with-rapidminer-part-... | null | CC BY-SA 2.5 | null | 2010-11-10T20:53:29.547 | 2010-11-10T20:53:29.547 | null | null | 74 | null |
4413 | 2 | null | 4259 | 2 | null | As far as books go, "The Elements of Statistical Learning" by Hastie, Tibshirani and Friedman is very good.
The full book is available on the [authors' web site](https://hastie.su.domains/ElemStatLearn/); you may want to take a look to see if it is at all suitable for your needs.
| null | CC BY-SA 4.0 | null | 2010-11-10T20:58:12.680 | 2022-12-03T04:29:36.237 | 2022-12-03T04:29:36.237 | 362671 | 439 | null |
4414 | 2 | null | 4259 | 2 | null | As for (on-line) references, I would recommend looking at Andrew Moore's tutorial slides on [Statistical Data Mining](https://web.archive.org/web/20100306025005/http://www.autonlab.org/tutorials/).
There are many textbooks on data mining and machine learning; maybe a good starting point is [Principles of Data Mining](h... | null | CC BY-SA 4.0 | null | 2010-11-10T21:11:31.560 | 2022-12-03T04:30:54.830 | 2022-12-03T04:30:54.830 | 362671 | 930 | null |
4415 | 2 | null | 4399 | 5 | null | Let $X_t$ be the time between events. Then for very regular events, $X_t$ will be approximately constant. e.g., if you do your laundry every Monday, then $X_t=7$ for all $t$. So you could just use the variance of $X_t$, where the small variance corresponds to highly regular and large variance corresponds to low regular... | null | CC BY-SA 2.5 | null | 2010-11-10T22:42:02.583 | 2010-11-11T06:02:57.460 | 2010-11-11T06:02:57.460 | 159 | 159 | null |
4417 | 1 | null | null | 50 | 21180 | In Bayesian statistics, it is often mentioned that the posterior distribution is intractable and thus approximate inference must be applied. What are the factors that cause this intractability?
| What are the factors that cause the posterior distributions to be intractable? | CC BY-SA 4.0 | null | 2010-11-11T00:33:28.430 | 2019-11-16T03:13:43.170 | 2019-11-16T03:13:43.170 | null | 1913 | [
"bayesian",
"approximation",
"inference"
] |
4418 | 1 | null | null | 0 | 1092 | Let $Z=(X+Y)/2$, where $X$ and $Y$ are independent normally-distributed random variables with known variances $\sigma^2_X$ and $\sigma^2_Y$ and unknown (and possibly different) means. Given a sample $x_1$ from $X$ and $y_1$ from $Y$, what is the minimum mean squared error estimator of the mean of $Z$? Is there a biased... | What is the minimum mean squared error estimator of the mean of two normally-distributed variables? | CC BY-SA 2.5 | null | 2010-11-11T01:35:14.477 | 2010-11-11T06:18:01.563 | 2010-11-11T06:18:01.563 | null | null | [
"estimation",
"mean",
"normal-distribution"
] |
4419 | 2 | null | 898 | 0 | null | I'm not sure what sort of data you need to process, but statistical algorithms are used quite frequently in robotics, media art, digital signal processing etc. It may be worthwhile to borrow from these domains.
| null | CC BY-SA 2.5 | null | 2010-11-11T02:16:48.133 | 2010-11-11T02:16:48.133 | null | null | 162 | null |
4420 | 2 | null | 4418 | 1 | null | Minimize SSE = Σi (zi-a)2 with respect to a and you get the average of the two sample means, so it looks like your MLE is also your minimum MSE estimator, whether you have one (x,y) pair or several. Not surprising, since the expression for the SSE and the log likelihood function are almost identical.
| null | CC BY-SA 2.5 | null | 2010-11-11T03:30:24.730 | 2010-11-11T03:30:24.730 | null | null | 5792 | null |
4421 | 2 | null | 898 | 0 | null | you have postrank
[http://data.postrank.com/content](http://data.postrank.com/content)
How do you sort what content is current and meaningful? We do it for you. PostRank gathers original content, as well as information at the feed and story level. This includes title, author, language, tags, and related links.
We anal... | null | CC BY-SA 2.5 | null | 2010-11-11T04:28:54.030 | 2010-11-11T04:28:54.030 | null | null | 1808 | null |
4422 | 1 | 4436 | null | 6 | 1933 | FULL DISCLOSURE: This is homework.
I have been provided with a small data set (n=21) the data are messy, looking at it in a scatterplot matrix provides me with little to no insight. I've been provided with 8 variables that are metrics created from a longditudinal study (BI, CONS, CL, CR, ..., VOBI). The other measureme... | Small sample linear regression: Where to start | CC BY-SA 2.5 | null | 2010-11-11T04:33:28.400 | 2013-10-07T10:11:18.717 | 2010-11-11T06:06:59.780 | 159 | 776 | [
"regression",
"self-study",
"methodology"
] |
4423 | 2 | null | 4347 | 8 | null | here is the best book I would recomend for the subject:
[http://www.amazon.com/Fuzzy-Sets-Logic-Theory-Applications/dp/0131011715](http://rads.stackoverflow.com/amzn/click/0131011715)
Here is an easy to read book:
[http://www.amazon.com/Fuzzy-Logic-Revolutionary-Computer-Technology/dp/0671875353](http://rads.stackoverf... | null | CC BY-SA 2.5 | null | 2010-11-11T04:45:20.507 | 2010-11-11T04:45:20.507 | null | null | 1808 | null |
4424 | 2 | null | 898 | 1 | null | [Bayesian networks](http://en.wikipedia.org/wiki/Bayesian_network) are perfect for online estimation, and offer a great diversity of models.
| null | CC BY-SA 2.5 | null | 2010-11-11T05:30:32.227 | 2010-11-11T05:30:32.227 | null | null | 1709 | null |
4425 | 2 | null | 4422 | 2 | null | If you're frustrated with too many correlations, and since you already have your covariance matrix (well almost) you could do a principal components analysis. You'll end up with fewer dimensions, which is probably fine considering your data set size, and what you end up with won't be intercorrelated anymore.
| null | CC BY-SA 2.5 | null | 2010-11-11T05:35:52.333 | 2010-11-11T05:35:52.333 | null | null | 1951 | null |
4426 | 2 | null | 4383 | 4 | null | I'd add one point.
Be aware of the distinction between group (e.g., comparing group means over time) and individual level measurement (e.g., correlating scores on the scale with other scales at the individual-level).
Reliability applies differently to the two levels.
Perhaps the following simplification helps:
- Relia... | null | CC BY-SA 2.5 | null | 2010-11-11T05:57:00.530 | 2010-11-11T05:57:00.530 | null | null | 183 | null |
4427 | 2 | null | 1980 | 9 | null | [Koenker and Zeileis](http://www.econ.uiuc.edu/~roger/research/repro/) provide a webpage with a relatively complete example.
They share:
- Rnw (Sweave code)
- R analysis code
- Final PDF
- Discussion of version control issues
| null | CC BY-SA 2.5 | null | 2010-11-11T06:22:29.180 | 2010-11-11T06:22:29.180 | null | null | 183 | null |
4428 | 2 | null | 4417 | 26 | null | The issue is mainly that Bayesian analysis involves integrals, often multidimensional ones in realistic problems, and it's these integrals that are typically intractable analytically (except in a few special cases requiring the use of conjugate priors).
By contrast, much of non-Bayesian statistics is based on [maximum... | null | CC BY-SA 2.5 | null | 2010-11-11T06:53:21.377 | 2010-11-11T06:53:21.377 | null | null | 449 | null |
4429 | 1 | 4430 | null | 30 | 3347 | It is helpful to study the data analysis code of experts.
I've recently been perusing [github](https://github.com/) and there are a number of people sharing data analysis code there. This includes a few R Packages (which of course are available directly from CRAN), but also several examples of reproducible research, pa... | Who to follow on github to learn about best practice in data analysis? | CC BY-SA 3.0 | null | 2010-11-11T06:59:46.883 | 2022-06-27T12:09:21.960 | 2018-09-21T22:34:07.653 | 11887 | 183 | [
"r",
"reproducible-research"
] |
4430 | 2 | null | 4429 | 19 | null | [Hadley Wickham](https://github.com/hadley). He has several exploratory data analysis projects on Github that you can look at (e.g., "data-baby-names"), and given the awesomeness of ggplot2/plyr/reshape, I have a default (but admittedly blind) trust in his best practices, particularly with respect to his own packages.
... | null | CC BY-SA 2.5 | null | 2010-11-11T07:35:57.207 | 2010-11-11T07:35:57.207 | null | null | 1106 | null |
4431 | 1 | 4486 | null | 1 | 821 | Way back when, I used to work in finance, and I remember helping a coworker use some kind of block bootstrap. (I believe the application was: we had weekly data on some financial indicator X, along with weekly data on some stock, and we wanted to measure how well X could be used to predict the stock's movements. And I ... | Resources to learn about block bootstrap in time series analysis | CC BY-SA 2.5 | null | 2010-11-11T07:50:43.590 | 2013-04-19T00:22:25.903 | null | null | 1106 | [
"time-series",
"regression",
"bootstrap"
] |
4432 | 2 | null | 4429 | 8 | null | [Diego Valle Jones](http://www.diegovalle.net/). His [Github](https://github.com/diegovalle), especially [analysis of homicides in Mexico](https://github.com/diegovalle/Homicide-MX-Drug-War) is really interesting.
| null | CC BY-SA 2.5 | null | 2010-11-11T07:59:55.433 | 2010-11-11T07:59:55.433 | null | null | 22 | null |
4433 | 2 | null | 4431 | 4 | null | Try the [Handbook of Computational Statistics, Part III, section 2.4](http://sfb649.wiwi.hu-berlin.de/fedc_homepage/xplore/ebooks/html/csa/node132.html).
| null | CC BY-SA 3.0 | null | 2010-11-11T08:21:47.770 | 2013-04-19T00:22:25.903 | 2013-04-19T00:22:25.903 | 159 | 159 | null |
4434 | 2 | null | 4431 | 1 | null | The textbook by [Shumway and Stoffer](http://rads.stackoverflow.com/amzn/click/0387293175) has a short section on bootstrapping time series (state-space) models. Also you may look to:
Pfeffermann, D. and Tiller, R. (2005) Bootstrap approximation to prediction MSE for State-Space models with estimated parameters, Journa... | null | CC BY-SA 2.5 | null | 2010-11-11T08:24:39.063 | 2010-11-11T08:24:39.063 | null | null | 892 | null |
4435 | 2 | null | 4429 | 10 | null | I also follow [John Myles White](https://stats.stackexchange.com/users/303/john-myles-white)'s GitHub [repository](https://github.com/johnmyleswhite). There are several data-oriented projects, but also interesting stuff for R developers:
- ProjectTemplate, a template system for building R project;
- log4r, a logging ... | null | CC BY-SA 2.5 | null | 2010-11-11T08:57:25.920 | 2010-11-12T10:35:00.423 | 2017-04-13T12:44:41.980 | -1 | 930 | null |
4436 | 2 | null | 4422 | 6 | null | I'd probably take a look at a ridge regression or, better, the lasso. These techniques are often used when there is multicollinearity. There are several options for doing this in R: See the Regularized and Shrinkage Methods section of the [Machine Learning & Statistical Learning](http://cran.r-project.org/web/views/Mac... | null | CC BY-SA 3.0 | null | 2010-11-11T09:20:18.010 | 2013-10-07T10:11:18.717 | 2013-10-07T10:11:18.717 | 17230 | 1390 | null |
4437 | 1 | 4438 | null | -1 | 6856 | so we have a0:
```
>a0[1,1:2]
l11 l12
-0.921 0.389593
```
Then;
```
> is.numeric(a0[1,1:2])
[1] FALSE
```
Ok, the text file containing them is a bit of a mess. Then:
```
> as.numeric(a0[1,1:2])
[1] 131 3
```
I know there was a trick to solve that. I just can't remember what it was...
EDIT: sample file:
```
... | R and as.numeric() | CC BY-SA 2.5 | null | 2010-11-11T09:26:39.780 | 2010-11-11T10:19:23.073 | 2010-11-11T09:45:06.437 | 603 | 603 | [
"r"
] |
4438 | 2 | null | 4437 | 4 | null | This is because you have read the numbers as factors; if you use `read.table`, try `header=T` or restructure the data before read. Some sample of the file should be helpful to resolve it.
Workaround would be to first convert factors to strings using `as.character` and then back to numbers with `as.numeric`.
Edit: Code ... | null | CC BY-SA 2.5 | null | 2010-11-11T09:32:00.040 | 2010-11-11T10:11:26.683 | 2010-11-11T10:11:26.683 | null | null | null |
4439 | 2 | null | 4437 | 3 | null | Would that help?
```
> a <- as.data.frame(matrix(scan("1.txt", what="character",
na.strings=c("NA",paste("V",1:6,sep=""))),
nc=13, byrow=T))
> class(a[,1])
[1] "factor"
> for (i in 1:ncol(a)) a[,i] <- as.numeric(as.character(a[,i]))
> class(a[,1])
[1] "numeric"
> ... | null | CC BY-SA 2.5 | null | 2010-11-11T10:11:18.593 | 2010-11-11T10:19:23.073 | 2010-11-11T10:19:23.073 | 930 | 930 | null |
4440 | 2 | null | 4422 | 5 | null | I find @ucfagls's idea most appropriate here, since you have very few observations and a lot of variables. Ridge regression should do its job for prediction purpose.
Another way to analyse the data would be to rely on [PLS regression](http://en.wikipedia.org/wiki/Partial_least_squares_regression) (in this case, PLS1), ... | null | CC BY-SA 2.5 | null | 2010-11-11T10:40:28.693 | 2010-11-11T10:40:28.693 | null | null | 930 | null |
4441 | 1 | 4444 | null | 5 | 2700 | I am collecting longitudinal data using for 4 time waves. Although the survey is administrated to the same population, different individuals may decide to complete it at each time point. As a result there are a number of individuals that only completed it once, others that completed it twice, some that completed it th... | How many data points do we need for mixed effects longitudinal data? | CC BY-SA 2.5 | null | 2010-11-11T10:41:58.623 | 2010-11-11T13:17:09.457 | null | null | 1871 | [
"r",
"mixed-model",
"panel-data"
] |
4442 | 2 | null | 4403 | -1 | null | Sounds like a classic data mining task:
Y_i = whether person i gets the question right,
X_i (vector) = set of past performance of person i.
Using a set of past data on n people (i=1,...,n), you can fit a predictive model of the sort Y = function of X.
A variety of models can be used to predict the performance of a new... | null | CC BY-SA 2.5 | null | 2010-11-11T12:58:08.970 | 2010-11-11T12:58:08.970 | null | null | 1945 | null |
4443 | 2 | null | 4337 | 0 | null | Aside from my practical statistical suggestion, I wanted to raise a slightly different issue: I realize that the cinema's goal is to maximize revenues, and of course the analysis (and strategy) can be geared towards that goal. However, I would like to suggest a broader, holistic view that companies as well as analysts ... | null | CC BY-SA 2.5 | null | 2010-11-11T13:12:53.023 | 2010-11-11T13:12:53.023 | null | null | 1945 | null |
4444 | 2 | null | 4441 | 9 | null |
- No, you don't need to remove individuals with data for only only one (or only a limited number) of timepoints. You're right to think that individuals with only one timepoint contribute nothing to estimation of the slope but they contribute to estimation of the intercept and you want to estimate both jointly. The mat... | null | CC BY-SA 2.5 | null | 2010-11-11T13:17:09.457 | 2010-11-11T13:17:09.457 | null | null | 449 | null |
4445 | 1 | 4449 | null | 14 | 1360 | A database of (population, area, shape) can be used to map population density by assigning a constant value of population/area to each shape (which is a polygon such as a Census block, tract, county, state, whatever). Populations are usually not uniformly distributed within their polygons, however. [Dasymetric mappin... | Model for population density estimation | CC BY-SA 4.0 | null | 2010-11-11T14:38:22.373 | 2022-11-23T09:46:24.493 | 2022-11-23T09:38:00.987 | 362671 | 919 | [
"modeling",
"unbiased-estimator",
"spatial"
] |
4446 | 1 | 4448 | null | 3 | 358 | The standard sum of squares as I know it is:
$$
\sum(X-m)^2
$$
where $m$ is the mean. I ran into a different one which can be written two ways:
$$
\sum(X^2) - \frac{(\sum X)^2}{n} = \sum(X^2) - m\sum X
$$
I believe the latter is called the "correction term for the mean" (e.g. [here](http://www.itl.nist.gov/div898/handb... | Sum of squares two ways, how are they connected? | CC BY-SA 3.0 | null | 2010-11-11T14:59:10.677 | 2017-11-12T17:22:55.250 | 2017-11-12T17:22:55.250 | 11887 | 1959 | [
"mathematical-statistics",
"sums-of-squares"
] |
4448 | 2 | null | 4446 | 5 | null | Expanding the square we get:
$\sum_i(X_i-m)^2 = \sum_i(X_i^2 + m^2 - 2 X_i m)$
Thus,
$\sum_i(X_i-m)^2 = \sum_i{X_i^2} + \sum_i{m^2} - 2 \sum_i{X_i m}$
Since $m$ is a constant, we have:
$\sum_i(X_i-m)^2 = \sum_i{X_i^2} + n m^2 - 2 m \sum_i{X_i}$
But,
$\sum_i{X_i} = n m$.
Thus,
$\sum_i(X_i-m)^2 = \sum_i{X_i^2} + n m^2 - ... | null | CC BY-SA 2.5 | null | 2010-11-11T15:15:36.757 | 2010-11-11T15:15:36.757 | null | null | null | null |
4449 | 2 | null | 4445 | 5 | null | You might want to check [work](http://www.informatik.uni-trier.de/%7Eley/db/indices/a-tree/l/Langford:Mitchel.html) of Mitchel Langford on dasymetric mapping.
He build rasters representing population distribution of Wales and some of his methodological approaches might be useful here.
Update: You might also have a look... | null | CC BY-SA 4.0 | null | 2010-11-11T16:13:57.317 | 2022-11-23T09:44:38.793 | 2022-11-23T09:44:38.793 | 362671 | 22 | null |
4450 | 2 | null | 4445 | 2 | null | Interesting question. Here is a tentative stab at approaching this from a statistical angle. Suppose that we come up with a way to assign a population count to each area $x_{ji}$. Denote this relationship as below:
$$z_{ji} = f(x_{ji},\beta)$$
Clearly, whatever functional form we impose on $f(.)$ will be at best an app... | null | CC BY-SA 4.0 | null | 2010-11-11T16:42:34.450 | 2022-11-23T09:46:24.493 | 2022-11-23T09:46:24.493 | 362671 | null | null |
4451 | 1 | null | null | 18 | 13551 | I am looking for social network datasets (twitter, friendfeed, facebook, lastfm, etc.) for classification tasks, preferably in arff format.
My searches via UCI and Google weren't successful so far... any suggestions?
| Social network datasets | CC BY-SA 3.0 | null | 2010-11-11T17:50:04.680 | 2015-09-29T07:10:33.623 | 2014-01-27T17:39:33.047 | 7290 | null | [
"classification",
"dataset"
] |
4452 | 2 | null | 4422 | 6 | null | It seems to me that the only thing worth doing here is testing a very focussed hypothesis, if you have one. But it seems like you don't.
With so few cases and so many variables, anything else would (in my opinion) be a fishing expedition. That could be a bit useful, perhaps, to generate an hypothesis to test with new ... | null | CC BY-SA 2.5 | null | 2010-11-11T18:07:36.833 | 2010-11-11T18:07:36.833 | null | null | 25 | null |
4453 | 1 | 4526 | null | 4 | 892 | Suppose I have a set $\mathcal{S}$ of $N$ distinct items. Now consider the set $\mathcal{P}$ of all possible pairs that I can draw from $S$. Naturally, $|\mathcal{P}| = \binom{N}{2}$. Now when I draw $k$ items (pairs) from $\mathcal{P}$ with a uniform distribution, what is the expected number of distinct items from $S$... | How to calculate the expected number of distinct items when drawing pairs? | CC BY-SA 2.5 | null | 2010-11-11T19:09:57.167 | 2010-11-30T18:21:49.360 | null | null | 977 | [
"binomial-distribution",
"expected-value"
] |
4454 | 1 | 4678 | null | 3 | 407 | Are there any decent tools for writing/designing questionnaires before providing to programmers? Currently Microsoft Word is being used and tracking changes and keeping it standardized has become a headache.
Update: I think I'm being a little misunderstood here. Here's a scenario: A client speaks to a statistician/expe... | What is a good tool and format for representing and communicating the design content of a survey? | CC BY-SA 3.0 | null | 2010-11-11T19:24:19.787 | 2012-05-01T06:58:11.560 | 2012-05-01T06:58:11.560 | 9007 | 305 | [
"survey",
"software",
"communication"
] |
4455 | 2 | null | 4454 | 1 | null | A combination of Perl + CGI is generally interesting for small surveys/questionnaires (because I hate PHP + MySQL). A gentle introduction can be found in [How to Conduct Behavioral Research over the Internet: A Beginner's Guide to Html and Cgi/Perl](http://www.web-research-design.net/).
Now, I think that Ruby and Rails... | null | CC BY-SA 2.5 | null | 2010-11-11T20:18:09.713 | 2010-11-11T20:38:22.387 | 2010-11-11T20:38:22.387 | 930 | 930 | null |
4456 | 2 | null | 4334 | 5 | null | You can build this model with AD Model Builder's random effects package.
This is free software available at [http://admb-project.org](http://admb-project.org). What you will
get is full information maximum likelihood solutions with the ability to try
MCMC methods afterwards if you wish. The idea is to regard this as a... | null | CC BY-SA 2.5 | null | 2010-11-11T20:45:50.343 | 2010-11-12T18:10:48.460 | 2010-11-12T18:10:48.460 | 1585 | 1585 | null |
4457 | 2 | null | 4451 | 3 | null | A large index of facebook pages was created and is available as a torrent (It is ~2.8Gb) [http://btjunkie.org/torrent/Facebook-directory-personal-details-for-100-million-users/3979e54c73099d291605e7579b90838c2cd86a8e9575](http://btjunkie.org/torrent/Facebook-directory-personal-details-for-100-million-users/3979e54c7309... | null | CC BY-SA 2.5 | null | 2010-11-11T20:53:17.367 | 2010-11-13T16:30:53.093 | 2010-11-13T16:30:53.093 | 1874 | 1874 | null |
4459 | 2 | null | 1980 | 10 | null | I have a few such examples [on my research papers page](http://jakebowers.org/papers.html). (I am not allowed to post more than one hyperlink as a new member. So I'll just describe the papers on that site.)
(1) "Making Effects Manifest in Randomized Experiments" uses R's vignette system.
(2) "Attributing Effects to a... | null | CC BY-SA 2.5 | null | 2010-11-11T21:30:55.937 | 2010-11-11T21:37:18.953 | 2010-11-11T21:37:18.953 | 930 | 909 | null |
4461 | 2 | null | 4454 | 1 | null | For mocking up what you want the survey to look like for a programmer, I would definitely just code it up in HTML.
- HTML is easy in general; for things like this, it will be dead simple. I don't think you'd need to fuss with any CSS to make something useful for your programmer. Conversely...
- You or your programm... | null | CC BY-SA 2.5 | null | 2010-11-11T22:02:31.417 | 2010-11-11T22:02:31.417 | null | null | 71 | null |
4462 | 1 | 4547 | null | 19 | 28761 | I do a bunch of real estate reporting and the median price is often reported, particularly by the NAR (National Association Of Realtors). As best I can tell, they only get the medians of real estate prices from each area. My question is, how should the national median be calculated, given the data restrictions? As a m... | Median of Medians calculation | CC BY-SA 3.0 | null | 2010-11-11T22:21:09.420 | 2015-09-18T22:50:01.793 | 2015-09-18T22:50:01.793 | 40230 | 1963 | [
"median"
] |
4463 | 2 | null | 4451 | 6 | null | Check out the Stanford large network dataset collection: [SNAP](http://snap.stanford.edu/data/).
| null | CC BY-SA 2.5 | null | 2010-11-11T22:33:57.397 | 2010-11-11T22:33:57.397 | null | null | 1913 | null |
4464 | 2 | null | 4451 | 6 | null |
- A huge twitter dataset that includes followers, not just tweets
- large collection of twitter datasets here
| null | CC BY-SA 2.5 | null | 2010-11-11T23:06:48.887 | 2010-11-14T11:22:27.570 | 2010-11-14T11:22:27.570 | 183 | 1808 | null |
4465 | 1 | 4479 | null | 9 | 1620 | I am a student, working with a team on a large-scale ecological experiment. We want to analyze survival data which has been derived from an experimental design with some pseudo-replication. This pseudo-replication was not discovered, unfortunately, until the middle of the experiment, at which point the design could not... | Any ideas about how to analyze survival data with pseudo-replication (dependent data)? | CC BY-SA 2.5 | null | 2010-11-11T23:10:10.583 | 2010-11-12T13:22:26.720 | 2010-11-11T23:48:57.587 | 449 | 1862 | [
"modeling",
"survival",
"experiment-design",
"independence",
"frailty"
] |
4466 | 1 | null | null | 31 | 1691 | Context:
In response to an earlier question about reproducible research [Jake wrote](https://stats.stackexchange.com/questions/1980/complete-substantive-examples-of-reproducible-research-using-r/4459#4459)
>
One problem we discovered when
creating our JASA archive was that
versions and defaults of CRAN packages
... | How to increase longer term reproducibility of research (particularly using R and Sweave) | CC BY-SA 2.5 | null | 2010-11-12T01:05:10.823 | 2017-05-18T21:16:39.290 | 2017-05-18T21:16:39.290 | 28666 | 183 | [
"r",
"reproducible-research",
"project-management"
] |
4467 | 2 | null | 4466 | 11 | null | One strategy involves using the `cacher` package.
- Peng RD, Eckel SP (2009). "Distributed reproducible research using cached computations," IEEE Computing in Science and Engineering, 11 (1), 28–34. (PDF online)
- also see more articles on
Roger Peng's website
Further discussion and examples can be found in the boo... | null | CC BY-SA 2.5 | null | 2010-11-12T01:14:44.813 | 2010-11-12T03:31:43.277 | 2010-11-12T03:31:43.277 | 183 | 183 | null |
4468 | 2 | null | 4466 | 18 | null | At some level, this becomes impossible. Consider the case of the famous Pentium floating point bug: you not only need to conserve your models, your data, your parameters, your packages, all external packages, the host system or language (say, R) as well as the OS ... plus potentially the hardware it all ran on. Now c... | null | CC BY-SA 2.5 | null | 2010-11-12T02:07:06.107 | 2010-11-12T03:11:01.320 | 2010-11-12T03:11:01.320 | 334 | 334 | null |
4469 | 1 | 4472 | null | 1 | 591 | Is there a way to type in a regression formula in SPSS in the same manner as R, with weights?
For example, in R, I would write something like:
```
lm(y ~ B1 + B2 + B1*B2, data=df, weights=x)
```
How would I go about recreating this in SPSS/PASW?
| Using R's formula style lm() with SPSS | CC BY-SA 2.5 | null | 2010-11-12T03:06:08.610 | 2012-06-12T14:18:11.463 | 2010-11-12T05:42:30.897 | 159 | 776 | [
"r",
"spss"
] |
4470 | 2 | null | 4469 | 7 | null | In SPSS you can have the GUI write the syntax for you via the paste button. If you go through the regression command in the window there is an option to include weights.
Here is some sample code it just had the program output for me:
```
REGRESSION
/MISSING LISTWISE
/REGWGT=VAR3
/STATISTICS COEFF OUTS R ANOVA
... | null | CC BY-SA 3.0 | null | 2010-11-12T03:48:13.660 | 2012-06-12T14:18:11.463 | 2012-06-12T14:18:11.463 | 1036 | 1036 | null |
4471 | 1 | null | null | 2 | 9247 | For chi squared distribution, how would I find quantiles for the following three cases:
A) $P(X^2> X^2_{\alpha})=0.01$ when $v = 21$
B) $P(X^2 < X^2_{\alpha})=0.95$ when $v =6$
C) $P(X^2_{\alpha} < X^2 <23.209) = 0.015$ when $v = 10$
Here $X^2_{\alpha}$ is the $\alpha$-quantile of the $\chi^2_{v}$ distribution.
| Calculating quantiles for chi squared distribution | CC BY-SA 2.5 | null | 2010-11-12T04:41:13.047 | 2021-02-02T02:49:17.333 | 2021-02-02T02:49:17.333 | 11887 | null | [
"self-study",
"quantiles",
"chi-squared-distribution"
] |
4472 | 2 | null | 4469 | 8 | null | In recent versions of SPSS you can run R code directly in SPSS on your SPSS datasets.
| null | CC BY-SA 2.5 | null | 2010-11-12T04:42:32.533 | 2010-11-12T04:42:32.533 | null | null | 183 | null |
4473 | 1 | 4474 | null | 4 | 2465 | I've created a model (cue ominous music) in R based on previous months data using lm(). Now, I would like to see how well it predicts the current months data.
For example, my model predicts sales figures. I have figures for January, February and March. My model is based on figures from January and February and I would... | Validating a linear model with R, lm() | CC BY-SA 3.0 | null | 2010-11-12T06:50:57.487 | 2011-04-13T15:01:29.147 | 2011-04-13T10:34:22.903 | 449 | 776 | [
"r",
"regression"
] |
4474 | 2 | null | 4473 | 8 | null | ?predict (which will implement ?predict.lm)
Make sure you put into "newdata" a data.frame with the exact same variable names.
| null | CC BY-SA 2.5 | null | 2010-11-12T07:08:19.540 | 2010-11-12T07:08:19.540 | null | null | 253 | null |
4476 | 2 | null | 4446 | 1 | null | Although the formula are equal, the practical difference is ease-of-calculation if you're doing it by hand. If all I had was a piece of paper and a pencil, I'd prefer the second formula--- $\sum X^2$ and $\sum X$ together take less time and are less error prone to calculate than $\sum (X - m)^2$.
| null | CC BY-SA 2.5 | null | 2010-11-12T12:37:14.680 | 2010-11-12T12:37:14.680 | null | null | 1916 | null |
4477 | 2 | null | 4471 | 7 | null | By hand, you need to refer to a tabulated distribution of the $\chi^2$, which should be found easily on the web (e.g., [this one](http://www.unc.edu/~farkouh/usefull/chi.html)). Let x denotes the quantile of interest, and v the degrees of freedom of the chi-square distribution.
You just have to know that the total area... | null | CC BY-SA 2.5 | null | 2010-11-12T12:47:56.360 | 2010-11-12T13:12:37.960 | 2010-11-12T13:12:37.960 | 930 | 930 | null |
4478 | 2 | null | 4466 | 13 | null | The first step in reproducibility is making sure the data are in a format that is easy for future researchers to read. Flat files are the clear choice here (Fairbairn in press).
To make the code useful over the long term, perhaps the best thing to do is write clear documentation that explains both what the code does an... | null | CC BY-SA 2.5 | null | 2010-11-12T12:54:03.257 | 2010-11-12T12:54:03.257 | null | null | 1916 | null |
4479 | 2 | null | 4465 | 3 | null | Here's some thoughts on what I'd do using relatively simple methods (i.e. avoiding frailty models, which I admit I've never used and don't really understand, so someone else may like to provide an answer involving them). I'm assuming you don't have other forms of censoring apart from the end of the experiment and that ... | null | CC BY-SA 2.5 | null | 2010-11-12T13:22:26.720 | 2010-11-12T13:22:26.720 | null | null | 449 | null |
4480 | 1 | 4481 | null | 2 | 1516 | Or more specifically, why would the index of a dataframe not be in ascending numerical order?
When I display the dataframe, the first row has column names, the data begins on second row, but the leftmost column (which doesn't have a header), is not in order, instead it shows as:
2
1
4
6
5
3
| What order are the rows in a dataframe in R displayed in? | CC BY-SA 2.5 | null | 2010-11-12T16:26:13.343 | 2010-11-12T16:35:15.587 | null | null | 1965 | [
"r"
] |
4481 | 2 | null | 4480 | 5 | null | Data frames have `rownames` attribute which is shown as the captionless leftmost column; you've propably altered the order of rows in data frame and it just shows the original indices. Try
```
rownames(df)<-NULL
```
to recreate it to 1:N.
| null | CC BY-SA 2.5 | null | 2010-11-12T16:32:03.157 | 2010-11-12T16:32:03.157 | null | null | null | null |
4482 | 2 | null | 4480 | 5 | null | If you reorder a data frame the row.names with be reordered to match. Note that if you haven't supplied rownames, R makes them up for you as characters `as.character(1:nrow(obj))`, where `obj` is your data frame. Hence these are row names.
```
> df <- data.frame(A = 5:1, B = LETTERS[1:5])
> df
A B
1 5 A
2 4 B
3 3 C
4... | null | CC BY-SA 2.5 | null | 2010-11-12T16:35:15.587 | 2010-11-12T16:35:15.587 | null | null | 1390 | null |
4483 | 2 | null | 4187 | 5 | null | I would use the "logit.mixed" function in [Zelig](http://cran.at.r-project.org/web/packages/Zelig/index.html), which is a wrapper for lime4 and makes it very convenient to do prediction and simulation.
| null | CC BY-SA 2.5 | null | 2010-11-12T16:50:03.513 | 2010-11-12T16:50:03.513 | null | null | 1966 | null |
4484 | 2 | null | 4466 | 7 | null | If you are interested in the virtual machine route, I think it would be doable via a small linux distribution with the specific version of R and packages installed. Data is included, along with scripts, and package the whole thing in a [virtual box](http://www.virtualbox.org/) file.
This does not get around hardware p... | null | CC BY-SA 2.5 | null | 2010-11-12T17:35:23.330 | 2010-11-12T17:35:23.330 | null | null | 1965 | null |
4485 | 1 | 4488 | null | 4 | 993 | As described in a few of my previous questions ([here](https://stats.stackexchange.com/q/3207/1381) and [there](https://stats.stackexchange.com/q/2917/1381)), I am interested in deriving summary statistics from statistics reported in the literature.
I would very much appreciate any advice into the validity or errors fo... | Is this the correct way to calculate $MSE$ from $SS_{\text{treatment(s)}}$, $df_{\text{treatment(s)}}$, $F$? | CC BY-SA 2.5 | null | 2010-11-12T18:35:44.143 | 2010-11-14T04:50:42.380 | 2017-04-13T12:44:33.237 | -1 | 1381 | [
"anova",
"meta-analysis",
"error",
"descriptive-statistics",
"degrees-of-freedom"
] |
4486 | 2 | null | 4431 | 4 | null | I have relied on [Resampling Methods for Dependent Data](http://books.google.com/books?id=e4f8sqm439UC&printsec=frontcover&dq=resampling+methods+for+dependent+data&source=bl&ots=hwangs1qCA&sig=WzmEiF0W2sRXlSm5MTvK6ESkt7k&hl=en&ei=_pPdTJnWIcGYnwfaqpCzDw&sa=X&oi=book_result&ct=result&resnum=1&ved=0CBIQ6AEwAA#v=onepage&q&... | null | CC BY-SA 2.5 | null | 2010-11-12T19:28:49.717 | 2010-11-12T19:28:49.717 | null | null | 1080 | null |
4487 | 2 | null | 4187 | 1 | null | Stephen Raudenbush has a book chapter in the Handbook of Multilevel Analysis on "[Many Small Groups](https://link.springer.com/book/10.1007/978-0-387-73186-5?from=SL)". If you are only interested in the effects of x on y and have no interest in higher level effects, his suggestion is simply to estimate a fixed effects ... | null | CC BY-SA 4.0 | null | 2010-11-12T20:09:03.653 | 2022-05-15T12:13:42.687 | 2022-05-15T12:13:42.687 | 79696 | 1036 | null |
4488 | 2 | null | 4485 | 6 | null | Your derivation is perfectly fine for regular (non-repeated meaures) ANOVA. For repeated measures ANOVA the F-statistics does not always equal $MS_g/MS_e$. Assuming weeks is the repeated measure, this formula is correct for the weeks and weeks*treatmeant terms (note that they will give the same MSE), but not for the tr... | null | CC BY-SA 2.5 | null | 2010-11-12T21:06:36.833 | 2010-11-12T21:06:36.833 | null | null | 279 | null |
4489 | 1 | 4490 | null | 18 | 119822 | Consider the following graph:
```
x <- 1:100
y1 <- rnorm(100)
y2 <- rnorm(100)+100
par(mar=c(5,5,5,5))
plot(x,y1,pch=0,type="b",col="red",yaxt="n",ylim=c(-8,2),ylab="")
axis(side=2, at=c(-2,0,2))
mtext("red line", side = 2, line=2.5, at=0)
par(new=T)
plot(x,y2,pch=1,type="b",col="blue",yaxt="n",ylim=c(98,108), ylab=... | Removing borders in R plots for achieving Tufte's axis | CC BY-SA 2.5 | null | 2010-11-13T01:46:15.850 | 2014-09-01T14:10:42.850 | null | null | 990 | [
"r",
"data-visualization"
] |
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