Changes in version 0.6.0                        

Major changes

  - Data sets with negative association between biomarker values and
    probability of target condition can be used without data
    manipulation

  - Order of panels in plot.diagmeta() can be specified by the user

Bug fixes

  - plot.diagmeta():
      - use chull() to determine the correct order of x- and y-values to
        print confidence regions for sensitivity and specificity in the
        SROC curve

User-visible changes

  - diagmeta(), ipd2diag();
    
      - new argument 'direction' to specify whether the probability of
        the target condition (e.g., a disease) is increasing or
        decreasing with higher values of the biomarker

  - ipd2diag();
    
      - new argument 'data' to provide data set with information on
        arguments 'studlab', 'value', and 'status'

  - diagmeta():
    
      - input to first argument 'TP' can be an object created with
        ipd2diag()

  - plot.diagmeta():
    
      - default set of graphs (argument 'which') changed from
        c("survival", "youden", "roc", "sroc") to c("regression", "cdf",
        "sensspec","youden", "roc", "sroc")
      - new argument 'ylim' to specify the y-limits of all plot
        (selected plots must have a similar y-axis)

Internal changes

  - New internal function plot.diagmeta-internal()

  - ipd2diag();
    
      - additional class 'ipd2diag' and attribute 'direction'

                 Changes in version 0.5-1 (2022-12-21)                  

User-visible changes

  - Change maintainer's email address

  - New branch 'release' on GitHub starting with diagmeta, version 0.5-1

Internal changes

  - Rename list element 'Cov.fixed' to 'Cov.common'

                 Changes in version 0.5-0 (2022-04-22)                  

Major changes

  - Behaviour of print.diagmeta() and print.summary.diagmeta() switched
    (to be in line with other print and summary functions in R)

  - Do not stop with an error if optimal cut-off cannot be determined
    for logistic distribution

  - Calculate area under the curve for specificity given sensitivity

Bug fixes

  - diagmeta():
      - fix for erratic confidence limits of AUC which could be outside
        the admissible range from 0 to 1 or exclude the AUC estimate

User-visible changes

  - More concise printout for summary.diagmeta()

Internal changes

  - diagmeta():
    
      - new list elements 'AUCSens' and 'AUCSpec' to calculate AUC for
        sensitivity given specificity or vice versa (existing list
        element 'AUC' is equal to 'AUCSens')

  - New internal function catch() to catch value for an argument

                 Changes in version 0.4-1 (2021-05-11)                  

Bug fixes

  - plot.diagmeta():
    
      - print correct confidence region for specificities in SROC curves

  - diagstats():
    
      - print results for requested specificity if only argument 'spec'
        is provided

User-visible changes

  - Use Markdown for NEWS

Internal changes

  - diagmeta():
      - new list element 'Cov.fixed' with covariance matrix from fixed
        effects model

                 Changes in version 0.4-0 (2020-04-02)                  

Major changes

  - New default model (argument 'model') in diagmeta(), i.e., common
    random intercept and common slope ("CICS"), due to estimation
    problems with the previous default ("DIDS") after changes in R
    package lme4

Bug fixes

  - plot.diagmeta():
      - correct line types for survival functions

User-visible changes

  - diagmeta():
    
      - print a more informative error message in case of a negative
        correlation between increasing cutoffs and sensitivity

  - plot.diagmeta():
    
      - argument 'points' considered for plots of type "regression",
        "cdf", "survival", "Youden", "ROC" and "sensspec"

  - Help pages:
    
      - use the default model in all examples

                 Changes in version 0.3-1 (2019-04-11)                  

User-visible changes

  - Export R functions:
    
      - as.data.frame.diagmeta(), plot.diagmeta(), print.diagmeta(),
        print.diagstats(), print.summary.diagmeta(), summary.diagmeta()

  - plot.diagmeta():
    
      - argument 'col.points' can be any color defined in colours()
      - new argument 'col.ci' to specify color of curves with confidence
        limits

Internal changes

  - diagmeta():
      - check for numerical values in arguments 'TP', 'FP', 'TN', 'FN',
        and 'cutoff'

                 Changes in version 0.3-0 (2018-12-11)                  

User-visible changes

  - plot.diagmeta(): new plot type to show sensitivity and specificity
    curves

  - New arguments 'sens' and 'spec' in diagstats()

  - print.summary.diagmeta():
    
      - print confidence interval for optimal cutoff (for normal
        distribution)

  - New function as.data.frame.diagmeta()

Bug fixes

  - plot.diagmeta():
      - correct ROC curves for datasets with decreasing cutoff values
        for individual studies (points (0, 0) and (1, 1) were connected
        with the wrong values on the ROC curve)

Internal changes

  - diagmeta():
      - calculate and return lower and upper confidence limit for
        optimal cutoff (for normal distribution)

                 Changes in version 0.2-0 (2018-03-23)                  

First version released on CRAN