Fit the Multinomial Tree Model 1 of Botella et al (2013)

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Description

The function fits the multinomial tree model 1 of Botella et al (2013) which assumes that both the sensitivity and specificity of the standard reference employed in the classification processes are equal to 1. The model is fitted by the EM algorithm implemented in the package mpt. Results should be compared to those of multinomial tree model 2 given by perfect.trees before making inference.

Usage

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perfect.trees(TP,FN,TN,FP,study, data)

## S3 method for class 'perfect.trees'
print(x,...)

Arguments

TP

the true positive counts reported in primary studies.Vector of integers,need to be speficied either directly or by referring to a variable in data frame.

FN

the false negative counts reported in primary studies.Vector of integers,need to be speficied either directly or by referring to a variable in data frame.

TN

the true negative counts reported in primary studies.Vector of integers,need to be speficied either directly or by referring to a variable in data frame.

FP

the false positive counts reported in primary studies.Vector of integers,need to be speficied either directly or by referring to a variable in data frame.

study

study names or identities.Vector of characters, need to be speficied either directly or by referring to a variable in data frame.

data

optional data frame that contains the above-mentioned variables.

x

an object of class "perfect.trees" (for print).

...

further arguments to be passed to or from other functions

Details

To specify the data, either directly input the TP, FN, FP, TN and study as vectors, or referring the corresponding variable names in a data frame.The multinomial tree models are then generated automatically according to the study number.

Value

An object of class "perfect.trees",basically a list with the model speficication and conventional model fit information, such as goodness of fit statistics and parameter estimates, etc. The print function does not return an object.

Author(s)

Huiling Huang <huiling.huang23@gmail.com>

References

Botella, J., Huang, H., Suero, M.(2013). Multinomial tree models for assessing the status of the reference in studies of the accuracy of tools for binary classification. Frontiers in Psychology.4:694. http://www.frontiersin.org/Journal/Abstract.aspx?s=956&name=quantitative_psychology_and_measurement&ART_DOI=10.3389/fpsyg.2013.00694

Botella, J., Huang, H., Suero, M. Meta-analysis of the accuracy of tools used for binary classification when the primary studies employ different references. To appear in Psychological Methods.

See Also

imperfect.trees.

Examples

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## load data of the accuracy of the screening tool Alcohol Use Disorders Identfication Test (AUDIT)
data(AUDIT)
## fitting the multinomial tree model 1
perfect.trees(TP=TP,FN=FN,TN=TN,FP=FP,study=study,data=AUDIT)
## data of the screening tool Mini Mental State Examination (MMSE) 
data(MMSE)
## fit the multinomial tree model 1, assuming imperfect reference
perfect.trees(TP=TP,FN=FN,TN=TN,FP=FP,study=study,data=MMSE)