fit.nmadasmodel: fit

In VNyaga/NMADAS: Arm-Based Network Meta-Analaysis of Diagnostic Accuracy Studies

Description

Fit a NMA model to the data.

Usage

fit.nmadasmodel(nma.model, data, S.ID, T.ID, Comparator = "NA", tp = NULL,
  fn = NULL, tn = NULL, fp = NULL, cores = 3, chains = 3,
  iter = 6000, warmup = 1000, thin = 10, ...)

Arguments

nma.model	A model written in the stan format from nmamodel. If the model is not specified, a hierachical beta-binomial model with frank copula is fitted.
data	A data-frame with no missing values containg TP, TN, FP, FN, SID and TID.
S.ID	A string indicating the name of the column with the study identifier.
T.ID	A string indicating the name of the column with the test identifier.
Comparator	The name of the comparator test when relative sensitivity and specificity are required. By default the first test as arranged alphabetically is the comparator.
tp	A string indicating the name of the columnt with the true positives.
fn	A string indicating the name of the columnt with the false negatives.
tn	A string indicating the name of the columnt with the true negatives.
fp	A string indicating the name of the columnt with the false positives.
cores	A positive numeric values specifying the number of cores to use to execute parallel sampling. When the hardware has more at least 4 cores, the default is 3 cores and otherwise 1 core.
chains	A positive numeric value specifying the number of chains, default is 3.
iter	A positive numeric value specifying the number of iterations per chain. The default is 6000.
warmup	A positive numeric value (<iter) specifying the number of iterations to be discarded(burn-in/warm-up). The default is 1000.
thin	A positive numeric value specifying the interval in which the samples are stored. The default is 10.
...	Other optional parameters as specified in stan.

Value

An object of nmadasfit class.

Author(s)

Victoria N Nyaga <[e-mail]>

References

Agresti A (2002). Categorical Data Analysis. John Wiley & Sons, Inc.

Clayton DG (1978). A model for Association in Bivariate Life Tables and its Application in Epidemiological Studies of Familial Tendency in Chronic Disease Incidence. Biometrika,65(1), 141-151.

Frank MJ (1979). On The Simultaneous Associativity of F(x, y) and x + y - F(x, y). Aequationes Mathematicae, pp. 194-226.

Farlie DGJ (1960). The Performance of Some Correlation Coefficients for a General Bivariate Distribution. Biometrika, 47, 307-323.

Gumbel EJ (1960). Bivariate Exponential Distributions. Journal of the American Statistical Association, 55, 698-707.

Meyer C (2013). The Bivariate Normal Copula. Communications in Statistics - Theory and Methods, 42(13), 2402-2422.

Morgenstern D (1956). Einfache Beispiele Zweidimensionaler Verteilungen. Mitteilungsblatt furMathematische Statistik, 8, 23 - 235.

Sklar A (1959). Fonctions de Repartition a n Dimensions et Leurs Marges. Publications de l'Institut de Statistique de L'Universite de Paris, 8, 229-231.

Examples

## Not run: 
data(demodata)

modelcode <- nmadasmodel()

fit1 <- fit(nma.model = modelcode
        S.ID='study',
		   T.ID = 'Test',
		   tp = 'TP',
		   tn = 'TN',
		   fp = 'FP',
		   fn = 'FN',
            data = demodata,
            iter = 6000,
            warmup = 2000,
            thin = 5,
            seed = 3)

modelcode <- nmadasmodel(copula = "fgm", marginals = "beta")

fit2 <- fit(nma.model = modelcode,
		   S.ID='study',
		   T.ID = 'Test',
		   tp = 'TP',
		   tn = 'TN',
		   fp = 'FP',
		   fn = 'FN',
            data = demodata,
            iter = 6000,
            warmup = 2000,
            thin = 5,
            seed = 3)

## End(Not run)

VNyaga/NMADAS documentation built on May 6, 2019, 11:20 a.m.