Version 1.4-4
Released 2017-03-15
      - Administrative change for expected power: cubature::adaptIntegrate 
        replaced by cubature::hcubature to reflect change of function name within
        package cubature.
      - Added function power.scABEL.sdsims() to calculate power for the BE decision 
        via scaled (widened) BE acceptance limits (EMA recommended) based on 
        subject data simulations.
      - Low CV (cosmetic) correction in power.scABEL() introduced.
      - Removed default CV = 0.3 from scABEL.ad() and sampleN.scABEL.ad().
        Stops exceution if CV not specified.
      - DOI for references added in many man pages. THX to Helmut.
      - Bens description of expected power added in /doc subdirectory
      - BE_power_sample_size_excerpt.pdf updated to reflect the changes in
        computation of OwensQ
      - Use of removed functions power.scABEL2() and sampleN.scABEL2() in
        pa.scABE() corrected.

Version 1.4-3
Released 2016-11-01
      - Little bug in power.TOST() removed which caused power <0 for large degrees 
        of freedom
      - Functions for expected power of the TOST procedure and sample size based 
        on expected power reworked to deal also with uncertainty of theta0 or 
        dealing with both uncertainties of CV and theta0. 
        Contributed mainly by Benjamin Lang.
      - Functions for expected power of non-inferiority testing and sample size 
        based on that expected power reworked to deal also with uncertainty of 
        theta0 or dealing with both uncertainties of CV and theta0. 
        Contributed mainly by Benjamin Lang.
      - Deprecated functions power.scABEL2() and sampleN.scABEL2() now removed.
        regulator = "ANVISA" no longer allowed in the scaled ABEL functions.
      - OwensQ() simpler/faster implemented. Now based soleyly on numerical
        integrataion in combination with non-central t.
      - Owen's T-function, used in OwensQOwen() now based on algorithm AS76 and 
        remarks to that algorithm to avoid numerical errors of the implementation 
        via integrate(). 
      - Data.frame ct9.6.6 in data("data2x2x3") added which was missing a long
        time ago.
      - Little inconsistency resolved (by Helmut) in output of power analysis 
        functions w.r.t. ratio or percent. Thanks to user myttiri of BEBA forum
        for pointing out this inconsistency. 
        
Version 1.4-2
Released 2016-07-14
      - Implementation_scaledABE_sims.pdf in \doc subdirectory updated to 
        reflect the changes in code of the scaled ABE functions.
      - The S3 method plot for class 'pwrA' now has an argument ratiolabel for 
        labeling the axis concerning theta0. Wish of B. Lang.
      - Various enhancements in man pages.
      - Power and sample size for FDA RSABE now take into account a CVcap
        if defined as finite.
      - Deprecated argument point in functions CI2CV()/CVfromCI() now removed
      - Misleading term 'Null (true) ratio' in output of sample size functions
        changed to 'True ratio'.
      - Minor bug in sampleN.2TOST() fixed.

Version 1.4-1
Published on GitHub 2016-06-14
      - Objects of class 'regSet' now have an additional component 'est_method'
        which controls the simulations via key statistics of the evaluation using
        EMA's ANOVA or FDA's recommended ISC in xyz.scABEL() functions.  
      - power.scABEL()/power.scABEL2() as well as sampleN.scABEL()/sampleN.scABEL2()
        are now unified. The regulator component 'est_method' is used for switching
        between sims based on EMA's ANOVA evaluation or ISC evaluation, respectively.
      - power.scABEL2()/sampleN.scABEL2() are therefore deprecated and will be
        removed in future versions. A corresponding warning is thrown.
      - URL of PowerTOST on GitHub added, URL for bug reports added.  

Version 1.3-7
Published on GitHub 2016-6-10        
      - Bug fix in functions scABEL.ad() and sampleN.scABEL.ad() if former
        regulator="ANVISA" settings are used.

Version 1.3-6
Released 2016-06-06 via CRAN
Released 2016-05-04 to beta-testers
      - Functions for power and sample size of BE decision of highly variable
        drugs or drug products via ABEL (average BE with expanding limits)
        updated to incorporate the reagulatory settings of Health Canada
        (new functions power.scABEL2() and sampleN.scABEL2(), based on simulations
        of intra-subject contrasts evaluation).
      - The same functions now accept as regulator argument an object of class
        'regSet' and allow via this way User definitions of regulatory settings.
      - New function reg_const made visible to define objects of 'regSet'.
        Class 'regSet' has an S3 print method.
      - Default value of argument theta0 in functions power.scABEL(), 
        power.scABEL2() and power.RSABE() changed to 0.90 to be in agreement
        with the setting in the corresponding sample size functions.
      - Function scABEL (calculation of widened acceptance limits) no longer
        accepts regulator="USER". This case may be handled via an object
        with class 'regSet', defined by help of function reg_const().
      - Functions CVfromCI()/CI2CV now use pe instead of point as argument due 
        to more consistency with their dual CI.BE(). For backward compatibility 
        point may be used also but then a warning is thrown. Argument point will 
        be removed in future versions.
      - Functions for expected power for TOST and non-inferiority updated
        to avoid numerical dificulties with integrate() if method="exact".
      - Documentation (typos in man pages) rigorously enhanced.
        Thanks to Helmut and Ben. 

Version 1.3-5
Released 2016-04-12
      - Functions for expected power for TOST and non-inferiority updated 
        (including corresponding sample size functions). Functions now include 
        an exact method that calculates the expected value of the power with 
        respect to the (prior) distribution of sigma^2 (inverse gamma distribution).
        Former only an approximation according to Julious/Owen was implemented. 
        Exact implementation contributed by B. Lang.
      - The functions for iteratively adjusting alpha for the EMA recommended
        ABEL method now have a new argument tol for convergence tolerance of the 
        internal used uniroot(). Was former hardcoded as tol=1e-5.
        Contributed by H. Schuetz.  
      - plot method of 'pwrA' objects reworked by H. Schuetz to avoid some 
        ugly overlays.

Version 1.3-4
Released 2016-03-09
      - Bug removed in all sample size estimation functions for scaled ABE which
        resulted for very low variability in NA for sample size. 
        Thanks to Shuanghe for detecting this bug.
      - All functions for scaled ABE now have an argument imax=100 for the maximum
        number of steps for sample size search. Wish of Helmut Schuetz.

Version 1.3-3
Released 2016-01-15 via CRAN
Released 2016-01-04 to alpha testers
      - New functions scABEL.ad() and sampleN.scABEL.ad() introduced to
        iteratively adjust alpha in order to maintain the consumer risk
        and adapt the sample size to compensate for the possible loss in
        power for the EMA method of scaled ABE (ABEL). 
        Contributed by Helmut Schuetz.
      - Default theta0 changed to 0.9 in sample size estimation for scaled ABE
        (as recommended by the Two Laszlo's).  

Version 1.3-02
Released 2015-12-02
      - New functions for calculation of power, type 1 errror and sample size
        for 2 TOST instances. Contributed by Benjamin Lang.

Version 1.3-01
Released 2015-09-30 
Released 2015-09-23 to alpha testers
      - New functions power.HVNTID() and sampleN.HVNTID() introduced to calculate 
        power and sample size for the BE decision via the FDA procedure for 
        highly variable NTID's (see FDA Dabigatran / rivaroxaban guidances).
      - power.HVNTID() and power.NTIDFDA() now return the power (p(BE)) and
        the components for the scaled ABE criterion, the conventional ABE test
        and the test for the ratio swT/swR <= 2.5 if the argument details=TRUE 
        (wish of Helmut Schuetz).
      - power.RSABE() now returns the power (p(BE)) and the components for the 
        scaled ABE criterion, for the point estimate criterion and for the 
        conventional ABE test alone if the argument details=TRUE.
        Analogous changes were made in power.scABEL(). See man pages.

Version 1.2-09
Released 2015-08-26
      - power.TOST() with method="exact" reworked to give correct values in 
        case alpha>0.5. OwensQOwen adapted to deal with upper integration
        limit R==Inf.
      - New power calculation method introduced, direct integration of the
        bivariate non-central t-distribution (pmvt() from package mvtnorm), 
        also an exact calculation method but with somewhat lower precision
        and longer run-time. Contributed by Benjamin Lang.
      - New function power.TOST.sim() to obtain the power via simulations of
        the TOST. Only intended for checking purposes.

Version 1.2-08
Released 2015-07-10
      - Maintenance release with NAMESPACE adapted to import the necessary
        functions from base R installation (CRAN request)
      - power.NTIDFDA() and sampleN.NTIDFDA() now have an design argument to
        choose between 2x2x4 (full replicate 4-period) and 2x2x3 (full replicate 
        3-period design)
      - Some minor documentation improvements

Version 1.2-07
Released 2015-06-03
      - Functions power.scABEL(), sampleN.scABEL() now allow the power and 
        sample size calculations for scaled ABEL according to the (inofficial)
        regulatory settings of Brasilian ANVISA
      - Function pa.scABE() also allows regulator="ANVISA"
      - New helper function scABEL for calculation of the (widened) ABE acceptance
        limits
      - Function power2.TOST() now removed

Version 1.2-06
Released 2015-01-23
      - Function power.TOST() now handles balanced as well as unbalanced studies
      - Function power2.TOST() is therefore depreciated and will not be contained
        in later versions
      - Internal change in interface to the (hidden) 'raw' power functions
        (sem used in function calls instead of se, n, bk)
      - BE_power_sample_size_excerpt.pdf in subdirectory doc changed to reflect
        the internal changes

Version 1.2-05
Released 2015-01-07
      - Bug in OwensQOwen() removed (debug code left over), THX to Helmut 
        for discovering this
      - Function CVfromCI() and alias CI2CV() now handle unbalanced studies,
        contributed by Benjamin Lang
      - Some typos in BE_power_sample_size_excerpt.pdf, found by Ben, corrected

Version 1.2-04
Released 2014-12-19
      - Bug in OwensT(h,a) for the case of a=-Inf removed. Thanks to
        Benjamin Lang for discovering that nasty bug
      - Functions power.noninf(), exppower.TOST(), exppower.noninf() adapted to 
        deal with unbalanced studies
      - Function pvalue.TOST() introduced to calculate the two p-values of the
        TOST procedure. Contributed by Benjamin Lang

Version 1.2-03
Released 2014-11-13
      - sampleN.dp() / power.dp() now cover "incomplete block designs"
      - minimum sample size in sampleN.dp() introduced to avoid errors for
        small CV <= 0.1 for the crossover design
      - partitition of n(total) to (sequence) groups reworked in most power  
        functions if design is unbalanced
      - Liu's 2x2x2 design with 2 repeated measurements in each period added
        (see ?known.designs under Notes)
       
Version 1.2-02
Released 2014-10-06
      - functions pa.XYZ() adapted so that they also function under R < 3.1.1
        (request of U. Ligges from CRAN) although with minpower>=0.5 

Version 1.2-01
Released 2014-09-30
      - Some minor bugs removed and spelling in man pages corrected
      - print method for class pwrA now calls plot()
      - power analysis in case of n=12 for the plan now drops n below 12 subjects

Version 1.2-00
Build 2014-09-19, released to alpha/beta testers only
      - Contains now functions for power analysis of a sample size plan
        for ABE (pa.ABE()), scaled ABE (pa.sABE()) and scaled ABE for NTID's
        (pa.NTIDFDA()) analyzing power for deviations from assumptions for 
        the sample size estimation
      - Contains further experimental functions for power calculations / samplesize 
        estimation for dose proportionality studies using the Power model

Version 1.1-13
Released 2014-08-12
      - Design constant bk(ni) for design="paired" corrected.
        THX to Helmut Schuetz who detected that bug.

Version 1.1-12
Released 2014-07-02
      - Some minor improvements in documentation.
      - Function power.TOST() now throws a warning if used with imbalanced
        designs (n not an even multiple of no. of sequences)
      - Internal change of start value of sample size search in sampleN.TOST()
        to avoid failed searches if variability is high and theta0 is near 1

Version 1.1-11
Released 2014-04-30
      - Utility function added which calculates 1-2*alpha confidence interval(s) 
        given point est., CV and n using log-tansformed evaluation.
      - Utility function added which calculates 1-2*alpha Fieller confidence 
        interval(s) given point est., CV (, CVb) and n for the ratio of
        un-transformed means.

Version 1.1-10
Released 2014-01-31
      - The package is now pre-compiled to 'byte code' via the compiler
        package for speed reasons. F.i. OwensQOwen() gains a sixfold boost.
      - Some bulk code changes to make the power calculations for extrem 
        cases more bullet proof without computation time burden.
      - Bug removed where noncentrality parameters in the power calculations
        became NaN (not a number).
      - OwensQ() now tries to return a value via nct-approximation if its value 
        is due to numeric difficulties falsely equal zero. 
        This approximation is up to 6 decimals correct as far as tested. 
        OwensQ() issues a warning if the nct-approximation is used.
      - Some improvements in documentation (man pages and *.pdf) to
        reflect the code changes

Version 1.1-09
Build 2014-01-03 Not released to the public.
      - OwensQ() now uses OwensQOwen() in case of high delta and/or high upper 
        integration limit. Thus extrem cases can be handled properly where 
        the former implementation via integrate() was prone to fail. 
        Thanks to Jiri Hofmann and Helmut Schuetz for pointing me to 
        such extrem cases.

Version 1.1-08
Released 2013-12-27
      - Dates typo in the history (NEWS) corrected from PowerTOST 1.1-00 on. 
        THX to Julien Grassot.
      - CVfromCI() now accepts either both CLs or one CL and the point 
        estimator, programmed by Helmut Schuetz.
      - power.RatioF() and sampleN.RatioF() now have an argument setseed=TRUE 
        which avoids the dependence if the power from the state of the 
        random number generator (due to the calculation method of pmvt() 
        from package mvtnorm). Thanks to Benjamin Lang.

Version 1.1-07
Released 2013-09-02
     - design 2x2x3 (TRT|RTR) implemented in power.scABEL(), sampleN.scABEL()
       and in power.RSABE(), sampleN.RSABE().
     - power.scABEL() now gives a warning if CVwT not equal CVwR in the design
       2x3x3, partial replicate.
     - Simulation details for the full replicate design slightly changed
       to obtain better numeric agreement of power to subject data sims. 

Version 1.1-06
Released 2013-06-21
     - Fat bug corrected in sampleN.NTIDFDA() which lead to false sample size
       for cases where the test of equal variabilities of Test vs. Reference
       comes into effect.

Version 1.1-05
Released 2013-06-17
     - The functions sampleN.scABEL(), sampleN.RSABE() and sampleN.NTIDFDA()  
       return now a data.frame with the input and the sample size result.
       The "Sample size" column contains the total sample size.
       The "nlast" column contains the last n value handled. May be useful for
       restarting.
     - Start values for sample size search in functions sampleN.scABEL(), 
       sampleN.RSABE() reworked. 
       Failed sample size searches are now more seldom observed. 
     - Flaw in sample size search removed which does not indicate a failed 
       search (n=NA) if started with a too high n (Thanks to Helmut Schütz).

Version 1.1-04
Released 2013-05-15 to alpha testers only
     - Functions power.NTIDFDA() and sampleN.NTIDFDA() introduced to calculate
       power and sample size for the BE decision via the method of the FDA for
       narrow therapeutic index drugs (NTID's). Power and sample size
       are based on simulations.

Version 1.1-03
Released 2013-05-03
     - Flaw in implementing the sims of 2x3x3 design with different intra-subject
       variabilities in functions power.RSABE() and sampleN.RSABE() as well as
       in functions power.scABEL() and sampleN.scABEL() disposed.
     - Methods and implementation details of the simulations for scaled ABE 
       documented in a PDF file in the /doc subdirectory of the package.
     - Simulation method for the EMA scaled ABEL changed to conform better
       with power values from simulations via subject data.  
     - Warning section in the help file of power.scABEL() introduced to
       appoint the fact that simulations via subject data and via the
       methods implemented in power.scABEL() gave empirical power values
       that are only approximately in agreement.   

Version 1.1-02
Released 2013-02-28
     - Functions power.RSABE() and sampleN.RSABE() introduced to calculate
       power and sample size for the BE decision via linearized scaled 
       ABE criterion as favored method of the FDA. Power and sample size
       are based on simulations.
     - Default of nsims changed to 1E5 (suggested by Helmut Schuetz).
     - Argument setseed introduced in the scaled ABE functions to avoid 
       different outcomes depending on the state of the (pseudo) random
       number generator. If setseed=TRUE a set.seed(123456) is issued before
       each call of the simulation functions.
     - Documentation improved.

Version 1.1-00
Released 2013-02-08
     - Functions power.scABEL() and sampleN.scABEL() introduced to calculate
       power and sample size for the BE decision via scaled (widened)
       BE acceptance limits based on simulations.
       Thanks to Helmut Schuetz for power testing these functions.
       http://forum.bebac.at/mix_entry.php?id=9997
     - False News file included. Sorry for that.

Version 1.0-01
not released, integrated in 1.1-00
     - Upper one-sided CL of the CV and therefore argument alpha2 removed from
       expsampleN.noninf() and expsampleN.TOST() because it lead to some
       confusion in users thinking this had to do with the algorithm via
       expected power.
     - CI2CV() as alias to CVfromCI() introduced because my self always typed 
       this name if aimed to calculate the CV from a given CI.
     - Function CVCL() now returns a 2 element vector also if an one sided
       interval is requested.   

Version 1.0-00
Released 2012-10-26
     - Bugfix in power.noninf() to get the correct power if theta0 is below
       margin (if margin <1) or theta0 is above margin (if margin >1).
       power.noninf() calculated up to now the power of an inferiority test.
       Thanks to Helmut Schuetz.
     - New helper functions CV2mse() and mse2CV.
     - New function CVCL() to calculate a confidence interval of a CV.   

Version 0.9-11
Released 2012-08-07
     - Bug fix in power.TOST(),  power2.TOST() and power.noninf() to use the 
       right df depending on argument robust. robust=FALSE had used the 
       robust df's. Thanks to Ben.

Version 0.9-10
Released 2012-07-20
     - Bug-fix in internal function .Q.integrand()
     - Bug fix in nmin - must be a multiple of steps to assure balance
       in sequence groups.
       Again thanks to Helmut Schuetz for detecting both.

Version 0.9-9
Released 2012-07-18
     - Workaround introduced to handle numeric problems in integrate()
       if CV<5.3E-6. Thanks to Helmut Schuetz.
     - Minimum sample size adapted to design used (f.i. n=2 if design="paired")  

Version 0.9-8
Released 2012-04-05 (Easter egg)
     - Functions added for 'expected' power and sample size calculations based 
       on it for the non-inferiority test for sake of completeness.
     - Functions CVpooled(), exppower.TOST() and expsampleN.TOST() now
       also implemented for logscale=FALSE, i.e. contain that argument in 
       their calls.
     - Function OwensQOwen() made public. This is an implementation of the 
       algorithm given by Owen itself in the original paper (Biometrica 1965) 
       via repeated integration by parts. 
       This function is only for comparative purposes.
     - Function OwensT() made public. It is needed internal in OwensQOwen()
       but may be useful for other purposes.   

Version 0.9-6/7
Released 2012-03-26
     - PowerTOST 0.9-7 is a small bug fix PowerTOST required from CRAN. 
       Contains the old PowerTOST number 0.9-6 in the package man page.
     - Functions added for power and sample size calculations based on 
       non-inferiority t-test. This is not a TOST procedure but eventually 
       useful if the question of 'non-superiority' within a BE study must be 
       evaluated.
       Hint: Evaluation of Fluctuation in the EMA MR NfG (1999) between 
       modified release formulation and immediate release product.

Version 0.9-4
Released 2012-03-05
     - Little bug in sampleN.TOST removed which causes extra doubled output
       of n and power if n=4. Thanks to Ben:
       http://forum.bebac.at/mix_entry.php?id=8206

Version 0.9-3
Released 2012-02-13
     - Bug in power.TOST removed which prevented calculation of Power
       according to method ^= "exact".
     - Sample size tables for replicate design 2x2x3 in data sub-directory added.
     - Sample size tables for replicate design 2x4x4 in data sub-directory added.
     - Scripts in the /test sub-directory made available.

Version 0.9-2
released 2011-12-24
     - Function power2.TOST() added to allow power calculations for 
       studies with unbalanced (sequence) groups.
     - Argument exact replaced by method in power.TOST(), sampleN.TOST().
       See help for these functions.
     - Attention! The sample size for the parallel group design is now
       the TOTAL sample size (to be consistent across all functions).
     - Sample size tables added for the 2x2 crossover and for the parallel 
       group design to alleviate validation/qualification of the package. 
       See data(package="PowerTOST").
     - Scripts added in the \tests sub-directory that create the sample size 
       tables from the data section.
     - Updated BE_power_sample_size_excerpt.pdf in the doc sub-directory.

Version 0.9-0
released 2011-12-15
     - Paired means design introduced
     - 'robust' argument added to nearly all functions.
       With robust=TRUE the degrees of freedom for the so-called robust
       evaluation (df2 in known.designs() output) will be used. 
       This may be helpful if planning is done for higher order designs 
       evaluated via mixed model or via intra-subject contrasts 
       (aka Senn's basic estimator).
     - Due to the necessary NAMESPACE from R14.0 on the internal functions 
       (names starting with .) are no longer exported.

Version 0.8-7
released 2011-10-20
     - Problem with slash in \name field of manual resolved 
       (requested by B. Ripley)

Version 0.8-6 
released 2011-05-18
     - Bug removed which gave incorrect exact power values in case of
       alpha>=0.5 (very unusual setting). Thanks again to Craig Zupke.
       Cross checked results of power at equivalence margins against 
       SAS Proc Power.

Version 0.8-5 
released 2011-05-16
     - Code in Owen's Q adapted to account for large delta or large b
       leading to integrand function almost zero over the whole range
       which then gave an error in integrate(). Thanks to Craig Zupke.

Version 0.8-4 
released 2011-03-11
     - Number of maximal steps in sample size search in the sample size 
       functions, formerly hard coded as 50, made accessible to users via 
       argument imax. but needs only adapted in rare extremal cases.
     - Start value for sample size search improved around theta0=1 (logscale)
       or theta0=0 (untransformed).

Version 0.8-3 
released 2011-01-18
     - Bug fix in known.designs().

Version 0.8-2 
released 2011-01-10
     - error in df for 3x3 and 4x4 crossover removed
     - function for pooling CV's from different studies made public
       see ?CVpooled

Version 0.8-1 
released 2010-11-25
     - helper function CVfromCI() added to estimate the CV from a confidence  
       interval. Useful if no CV but CI was given in literature.

Version 0.7-3 
released 2010-10-09
     - bugs in documentation removed
     - input argument diff removed from sampleN.TOST, expsampleN.TOST,
       power.TOST and exppower.TOST

Version 0.7-2 
released 2010-08-27
     - little bug causing warnings in case of 2x2 alias 2x2x2 removed

Version 0.7-1 
released 2010-08-12
     - functions added for the power and sample size for the ratio of 
       two means with normally distributed data on the original scale 
       (based on Fieller's confidence (fiducial) interval).
       AFAIK until now only implemented in the commercial nQuery.
     - Note that the parameter diff (Null ratio / Null diff.) is now
       named theta0 since it was annoying for users to call it diff in case
       of ratios (logscale=TRUE). The parameter diff is still supported
       but will be ceased in the next release. Therefore a warning is issued 
       if diff is used.
       
Version 0.6-2 
released 2010-07-21
     - some internal code consolidation
     - internal hidden functions .CV2se() and .se2CV() made public
     - minor enhancements in help pages 
     - more examples
     - short documentation of used statistical apparatus
       BE_power_sample_size_excerpt.pdf
       for classical power / sample size in directory /doc added

Version 0.5-1 
     - first release to CRAN on 2010-05-07
