search for: biserials

Dear list, has anyone written a package/function in R for computing a point- biserial resp. biserial correlation? Thanks in advance Bernd

Hello, I found in the forum two threads about point biserial correlation. One of them (1) mentioned "a point-biserial correlation is just a Pearson correlation where one of the variables is dichotomous. Thus, the command is just the normal cor function". The other (2) mentioned "Professor Fox's package polycor" as a way to calculate point biserial correlation?

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Dear R-listers, Can someone suggest a method for generating a finite Bernoulli sequence that is likely to have a given point-biserial correlation with an existing Bernoulli sequence? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall

Dear developers of R-project, I have such data height of male persons 181, 178, 182, 160, 187, 193, 184, 184, 175, 178, 184, 184, 174, 185, 175 height of female persons 164, 165, 160, 174, 167, 161, 164, 165, 169, 175, 165, 155, 172, 164, 172, 166, 160, 159, 158, 173 I want to determine if height is dependent on gender, and I need to find, as I understand, point biserial correlation. I had tried

Hi, What package would you recommend for analyzing the validity/reliability of multiple choice tests. Doing things such as classical test analysis, factor analysis, item response theory. I've used psychometric (item.exam), MiscPsycho (alpha.Summary), and ltm (rcor.test). MiscPsycho reported the numbers most similar to what I get in SPSS: corrected point biserial correlations,

Dear community I'm pretty new to R and I'm trying to do a Point-baserial correlation for a nominal dichotomous variable with a interval scaled variable. It works fine, but the output just shows me the correlation and nothing else (p-Value would be important). I tried it with the following codes: - biseral.cor() - cor.biseral() - I also tried a polyserial() I've found on this

...king scales (e.g., Stocking-Lord), lattice graphics for item characteristic curves, and bayesian scoring methods (EAP). Below is a sample session: set.seed(1) # for replication only xx <- simRasch(200, 10) # Simulate data for 200 persons and 10 items classical(xx$data) # get p-values and point-biserials alpha(xx$data) # coefficient alpha alpha.Summary(xx$data) aa <- jml(xx$data) # estimate item parameters scoreCon(aa$params) The student in row 1 has a number correct score of 3 out of 10. From the score conversion table, his theta estimate is -1.36. So, we can ask, what is the probability that...

...king scales (e.g., Stocking-Lord), lattice graphics for item characteristic curves, and bayesian scoring methods (EAP). Below is a sample session: set.seed(1) # for replication only xx <- simRasch(200, 10) # Simulate data for 200 persons and 10 items classical(xx$data) # get p-values and point-biserials alpha(xx$data) # coefficient alpha alpha.Summary(xx$data) aa <- jml(xx$data) # estimate item parameters scoreCon(aa$params) The student in row 1 has a number correct score of 3 out of 10. From the score conversion table, his theta estimate is -1.36. So, we can ask, what is the probability that...

Hello R-User! I appologise in advance if this should also go into statistics but I am presently puzzled. I have a data.frame (about 300 rows and about 80 variables) and my variables are dichotomous factors, continuous (numerical) and ordered factors. I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm())

Hi I am looking for a structural equation modeling package in R which can be used for categorical data. Is anyone aware of the existence of such a package? Would appreciate any help on this. Thank you Upasna -- --------------------------------------------------------------------- Upasna Sharma Research Scholar Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay

My data set has a mixed level of measurement: Nominal scale - location (city) Ordinal scale - temperature (low, medium, high) Interval scale - age & value Just curious if there is an R package available that will handle the mixed "Level of Measurement". Looking to do graphical presentation of the correlation and also a qualitative analysis of the correlation.  Thanks again for

Dear R-users Could anyone tell me which library contains a function to compute polycoric correlations? I wonder the same question was asked a while ago, but I could not locate the mail in the R-help archives. Sorry for bothering you. Sincerely ------------------------ Hiroto Miyoshi ???? h_m_ at po.harenet.ne.jp

Hi, we are trying to do structural equation modelling on R. However, one of our predictor variables is categorical (smoker/nonsmoker). Now, if we want to run the sem() command (from the sem library), we need to specify a covariance matrix (cov). However, Pearson's correlation does not work on the dichotomous variable, so instead we produced a covariance matrix using the Spearman's (or

I am looking to fit one or more latent categorical variables to data that is a mixture of categorical and continuous variables. Factor analysis would work for continuous data, latent class analysis for categorical data. I understand that in a package such as MPlus I could perform a single analysis of both data types. Are there similar routines available in R? Stuart -----Original Message-----

Full_Name: Dirk Koschuetzki Version: 2.1.1 OS: source code Submission from: (NULL) (194.94.136.34) Hello, >From the source code (R-2.1.1, file: .../R-2.1.1/src/library/stats/R/) ****************************** cor.test.default <- function(x, y, alternative = c("two.sided", "less", "greater"), method = c("pearson", "kendall",

Hello, I am running polychoric correlations on a dataset composed of 12 ordinal and binary variables (N =384), using the polycor package. One of the association (between 2 dichotomous variables) is very high using the 2-step estimate (0.933 when polychoric run only between the two variables; but 0.801 when polychoric run on the 12 variables). The same correlation run with ML estimate returns a

Hi list members I have a vector of strings x=c("w","ex","ee") And I want to get a logical vector showing the positions where my search string "e" matches the elements partially, i.e. is at least the left-hand part of the target strings, i.e. I want to get a vector FALSE TRUE TRUE. Any ideas? Thanks Steve Powell proMENTE social research research |