R Dataset / Package MASS / muscle
Attachment | Size |
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dataset-29991.csv | 789 bytes |
Documentation |
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On this Picostat.com statistics page, you will find information about the muscle data set which pertains to Effect of Calcium Chloride on Muscle Contraction in Rat Hearts. The muscle data set is found in the MASS R package. Try to load the muscle data set in R by issuing the following command at the console data("muscle"). This may load the data into a variable called muscle. If R says the muscle data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data with library("MASS") followed by data("muscle"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing muscle at the command-line which should display the entire dataset. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the muscle R data set. The size of this file is about 789 bytes. Effect of Calcium Chloride on Muscle Contraction in Rat HeartsDescriptionThe purpose of this experiment was to assess the influence of calcium in solution on the contraction of heart muscle in rats. The left auricle of 21 rat hearts was isolated and on several occasions a constant-length strip of tissue was electrically stimulated and dipped into various concentrations of calcium chloride solution, after which the shortening of the strip was accurately measured as the response. Usagemuscle FormatThis data frame contains the following columns:
SourceLinder, A., Chakravarti, I. M. and Vuagnat, P. (1964) Fitting asymptotic regression curves with different asymptotes. In Contributions to Statistics. Presented to Professor P. C. Mahalanobis on the occasion of his 70th birthday, ed. C. R. Rao, pp. 221–228. Oxford: Pergamon Press. ReferencesVenables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth Edition. Springer. ExamplesA <- model.matrix(~ Strip - 1, data=muscle) rats.nls1 <- nls(log(Length) ~ cbind(A, rho^Conc), data = muscle, start = c(rho=0.1), algorithm="plinear") (B <- coef(rats.nls1))st <- list(alpha = B[2:22], beta = B[23], rho = B[1]) (rats.nls2 <- nls(log(Length) ~ alpha[Strip] + beta*rho^Conc, data = muscle, start = st))Muscle <- with(muscle, { Muscle <- expand.grid(Conc = sort(unique(Conc)), Strip = levels(Strip)) Muscle$Yhat <- predict(rats.nls2, Muscle) Muscle <- cbind(Muscle, logLength = rep(as.numeric(NA), 126)) ind <- match(paste(Strip, Conc), paste(Muscle$Strip, Muscle$Conc)) Muscle$logLength[ind] <- log(Length) Muscle})lattice::xyplot(Yhat ~ Conc | Strip, Muscle, as.table = TRUE, ylim = range(c(Muscle$Yhat, Muscle$logLength), na.rm = TRUE), subscripts = TRUE, xlab = "Calcium Chloride concentration (mM)", ylab = "log(Length in mm)", panel = function(x, y, subscripts, ...) { panel.xyplot(x, Muscle$logLength[subscripts], ...) llines(spline(x, y)) }) -- Dataset imported from https://www.r-project.org. |
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