Trimmed Spearman-karber Program
( ) ## Default S3 method: (x, n, r, control = 0, trim = 0, conf.level = 0.95, use.log.doses =, ) ## S3 method for class 'data.frame' (input, control = 0, trim = 0, conf.level = 0.95, use.log.doses =, ) ## S3 method for class 'tskresult' (x, ) Arguments x a non-empty numeric vector of doses. N a non-empty numeric vector of number of subjects at each dose, of the same length as x, or a number if the number of subjects are the same at each dose. R a non-empty numeric vector of the number of responding subjects at each dose. Input Data frame containing the data to be analyzed. Must contain the three components x (doses), n (number of subjects at each dose), and r (number of subjects that respond). Control fraction of subjects responding in a control experiment trim a number between 0 and.5. 0 gives the untrimmed Spearman-Karber method.
Spearman Karber Equation
Conf.level confidence level to use for confidence intervals. Use.log.doses if TRUE then the log of the doses in x will be taken and used for calculation. Further arguments to be passed to or from methods. Value A list of type 'tskresult' containing the following components: use.log.doses same as above. Trim same as above. LD50 The estimated effective dose for 50 percent of the population.
Toxicity of cigarette butts, and their chemical components, to marine and freshwater fish. Novotny TE, Lum K, Smith E, et al. Int J Environ Res Public Health 2. Citation: hamilton, m., r. Russo, and r. Trimmed spearman-karber method for estimating median lethal concentrations in toxicity bioassays.
Gsd The geometric standard deviation of the LD50 estimate. Conf.level same as above. Conf.int A confidence interval for the measurement, at the level of conf.level. If use.log.doses = FALSE, instead of LD50 and gsd, the list will contain: mu The estimated LD50, given a different name to prevent confusion with calculations on a log scale sd The standard deviation of the mu estimate. Note This code expects the data to have an increasing slope once smoothed. However, some studies may result in data with a decreasing trend.
For instance, one user had data measuring the survival of freshwater fish under increasing water salinity: at low salinity all fish survive, while at high salinity all fish die. If using data with a decreasing trend, simply use the opposite response, e.g., swap the count that survive for the count that do not, or replace r with n-r. Note This code was validated using the data given in Hamilton et al.
(1977) Note that the confidence intervals given in Hamilton et al. (1977) are incorrect, as per Hamilton et al. This code replicates the results of the DOS program provided by the US EPA to perform the Spearman-Karber method, available. Author(s) Brenton R. Stone, References Hamilton, M. A.; Russo, R. C.; Thurston, R.
Trimmed Spearman-Karber Method for Estimating Median Lethal Concentrations in Toxicity Bioassays. 1977, 11 (7), 714-719. Ibid, 1978, 12 (4), 417.
Spearman Karber Method
The MATLAB function in TSK.m analyzes a dose-response curve and calculates the median dose (for instance, the lethal dose for 50% of the population (LD50)) using the Trimmed Spearman-Karber method. This is an alternative to dose-response analysis methods such as probit and logit methods. It does not require glmfit or the stats toolbox.All calculations in this code are based on the method from Hamilton, M.A.; Russo, R.C.; Thurston, R.V. Trimmed Spearman-Karber Method for Estimating Median Lethal Concentrations in Toxicity Bioassays.
Trimmed Spearman-karber
1977, 11 (7), 714-719: See also ibid, 1978, 12 (4), 417: code was validated using the data given in Hamilton et al. (1977) and the example given in the documentation for the EPA's DOS program to perform the Spearman-Karber method, available at (Note that the confidence intervals given in Hamilton et al. (1977) are incorrect, as per Hamilton et al. (1978).) This code replicates the EPA program's results. Hamilton's test cases are provided in TSKTest.m. Tags: Validated, Epa, Documentation, Enviro, Bioassays, Median, Estimating Platforms: BSD, Mac OS X, Solaris, linux.
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