Changes in version 1.1.4                        

  - Prediction interval: Wang and Lee (2019)

                 Changes in version 1.1.3 (2019-09-17)                  

  - Prediction & Confidence interval: the pima and cima functions
      - Back-transformartion for logarithmic scale outcomes (print &
        plot function; thanks to Dr. Morio Aihara).
  - CITATION was updated.
  - Vignette was updated.

                 Changes in version 1.1.2 (2019-03-11)                  

  - Prediction interval: the pima function
      - Parallel computing for the parametric bootstrap method (see a
        Vignette file).
      - Forest plot (see a Vignette file).
      - Kenward-Roger's approach.
  - Confidence interval: the cima function
      - A Wald-type t-distribution confidence interval. Variance
        estimator of the average effect: an approximate estimator.
        Heterogeneity variance: Dersimonian-Laird estimator.
      - A Wald-type t-distribution confidence interval. Variance
        estimator of the average effect: an approximate, Hartung-Knapp,
        Sidik-Jonkman, Kenward-Roger estimators. Heterogeneity variance:
        REML estimator.
      - Profile likelihood confidence interval.
      - Profile likelihood confidence interval with a Bartlett type
        correction.
      - Forest plot.
  - Heterogeneity variance estimators: the tau2h function
      - DerSimonian-Laird estimator.
      - Variance component type estimator.
      - Paule--Mandel estimator.
      - Hartung-Makambi estimator.
      - Hunter--Schmidt estimator.
      - Maximum likelihood estimator.
      - Restricted maximum likelihood estimator.
      - Approximate restricted maximum likelihood estimator.
      - Sidik--Jonkman estimator.
      - Sidik--Jonkman improved estimator.
      - Empirical Bayes estimator.
      - Bayes modal estimator.
      - ML and REML confidence intervals.
  - Converting binary data: the convert_bin function
      - Converting binary data to logarithmic odds ratio (see a Vignette
        file).
      - Converting binary data to logarithmic relative risk.
      - Converting binary data to risk difference.
  - The distribution of a positive linear combination of chiqaure random
    variables: the pwchisq function

                 Changes in version 1.1.1 (2018-09-14)                  

  - Fixed documents.

                 Changes in version 1.1.0 (2018-09-14)                  

  - Refined the package structure.
  - New function pima is available (see a Vignette file).

                 Changes in version 1.0.1 (2018-05-10)                  

  - Updated citation informations.

                 Changes in version 1.0.0 (2018-04-06)                  

  - First release.