diff --git a/Project.toml b/Project.toml
index e599a68..e4f0832 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 authors = ["Vladimir Arnautov (mail@pharmcat.net)"]
 name = "ClinicalTrialUtilities"
 uuid = "535c2557-d7d0-564d-8ff9-4ae146c18cfe"
-version = "0.2.0"
+version = "0.2.1"
 
 [deps]
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
diff --git a/cange.log b/cange.log
index 1e234eb..e4bd932 100644
--- a/cange.log
+++ b/cange.log
@@ -1,3 +1,10 @@
+v0.2.1
+  - error message for besamplen
+  - cvfromci new method
+  - pooledcv new method
+  - minor fix
+  - cosmetics
+
 v0.2.0
 
   Breaking changes(!):
diff --git a/src/samplesize.jl b/src/samplesize.jl
index 75fadf7..aaf5cd1 100644
--- a/src/samplesize.jl
+++ b/src/samplesize.jl
@@ -633,7 +633,7 @@ Bioequivalence sample size estimation.
 function besamplen(;alpha::Real=0.05, beta::Real=0.2, theta0::Real=0.95, theta1::Real=0.8, theta2::Real=1.25, cv::Real=0.0, sd::Real=0.0, design::Symbol=:d2x2, method::Symbol=:owenq, logscale::Bool=true)::TaskResult
     if !(0 < beta < 1) throw(ArgumentError("Beta ≥ 1.0 or ≤ 0.0!")) end
     if !(0 < alpha < 1) throw(ArgumentError("Alfa ≥ 1.0 or ≤ 0.0!")) end
-    if theta1 ≥ theta2  throw(ArgumentError("theta1 ≥ theta2!")) end
+    if !(theta2 > theta0 > theta1)  throw(ArgumentError("!(theta2 > thetao > theta1), check settings!")) end
     if !logscale && cv > 0.0 && sd ≤ 0.0 throw(ArgumentError("Use sd instead cv for non-logscale parameters!")) end
     if !logscale && sd ≤ 0.0 throw(ArgumentError("sd ≤ 0.0!")) end
     if !logscale && cv > 0.0 @warn "sd and cv provided for non-logscale parameters, only sd used!" end
diff --git a/src/show.jl b/src/show.jl
index 3f81042..c95389d 100644
--- a/src/show.jl
+++ b/src/show.jl
@@ -73,7 +73,7 @@ function Base.show(io::IO, obj::TaskResult{CT}) where CT <:  CTask{T, D, Bioequi
         println(io, objectivename(obj.task.objective))
         println(io,"-----------------------------------------")
         println(io,"  Parameter type: ",  paramname(obj.task.param))
-        println(io,"  Design: ",  designinfo(obj.task.design))
+        println(io,"  Design: $(obj.task.design)")
         println(io,"  Hypothesis: ", obj.task.hyp)
         #println(io,"  Lower limit: ", round(obj.task.llim, sigdigits = 4))
         #println(io,"  Upper limit: ", round(obj.task.ulim, sigdigits = 4))
diff --git a/src/utilities.jl b/src/utilities.jl
index d6a5c82..19fef2d 100644
--- a/src/utilities.jl
+++ b/src/utilities.jl
@@ -84,6 +84,9 @@ function cvfromci(;alpha = 0.05, theta1 = 0.8, theta2 = 1.25, n, design=:d2x2, m
     if mso return ms end
     return cvfromvar(ms)
 end
+function cvfromci(theta1, theta2, n; alpha = 0.05, design=:d2x2, mso=false, cvms=false)
+    return cvfromci(;alpha = alpha, theta1 = theta1, theta2 = theta2, n = n, design = design, mso = mso, cvms = cvms)
+end
 
 """
     pooledcv(data::DataFrame; cv=:cv, df=:df, alpha=0.05, returncv=true)::ConfInt
@@ -104,13 +107,24 @@ Pooled CV from multiple sources.
 - false - return var
 
 """
-function pooledcv(data::DataFrame; cv=:cv, df=:df, alpha=0.05, returncv=true)::ConfInt
+function pooledcv(data::DataFrame; cv = :cv, df = :df, alpha::Real = 0.05, returncv::Bool = true)::ConfInt
     if isa(cv, String)  cv = Symbol(cv) end
     if isa(df, String)  df = Symbol(df) end
-    tdf = sum(data[:, df])
-    result = sum(varfromcv.(data[:, cv]) .* data[:, df])/tdf
+    return pooledcv(data[!, cv], data[!, df]; alpha = alpha, returncv = returncv)
+end
+function pooledcv(cv::Vector, df::Vector; alpha=0.05, returncv = true)::ConfInt
+    tdf = sum(df)
+    result = sum(varfromcv.(cv) .* df)/tdf
     CHSQ = Chisq(tdf)
     if returncv return ConfInt(cvfromvar(result*tdf/quantile(CHSQ, 1-alpha/2)), cvfromvar(result*tdf/quantile(CHSQ, alpha/2)), cvfromvar(result))
     else ConfInt(result*tdf/quantile(CHSQ, 1-alpha/2), result*tdf/quantile(CHSQ, alpha/2), result)
     end
 end
+function pooledcv(cv::Vector, n::Vector, design::Vector; alpha=0.05, returncv = true)::ConfInt
+    d  = Design.(design)
+    df = Array{Int, 1}(undef, length(d))
+    for i = 1:length(d)
+        df[i] = d[i].df(n[i])
+    end
+    return pooledcv(cv, df; alpha = alpha, returncv = returncv)
+end
diff --git a/test/citest.jl b/test/citest.jl
index c646fb8..73d7782 100644
--- a/test/citest.jl
+++ b/test/citest.jl
@@ -44,97 +44,97 @@ println(" ---------------------------------- ")
     #---- twoProp
     #-- mn
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:or, method=:mn)
+    ci = ClinicalTrialUtilities.orpropci(30, 100, 40, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 0.29537414 atol=1E-6
     @test ci.upper    ≈ 0.97166697 atol=1E-6
     @test ci.estimate ≈ 0.53571428 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(100, 100, 90, 90; alpha=0.05, type=:or, method=:mn)
+    ci = ClinicalTrialUtilities.orpropci(100, 100, 90, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 0.0
     @test ci.upper    ≈ Inf
     #@test ci.estimate == NaN
 
-    ci = ClinicalTrialUtilities.twoprop(0, 100, 90, 90; alpha=0.05, type=:or, method=:mn)
+    ci = ClinicalTrialUtilities.orpropci(0, 100, 90, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 0.0
     @test ci.upper    ≈ 0.00041425995552740226  atol=1E-6
     @test ci.estimate ≈ 0.0
 
-    ci = ClinicalTrialUtilities.twoprop(100, 100, 0, 90; alpha=0.05, type=:or, method=:mn)
+    ci = ClinicalTrialUtilities.orpropci(100, 100, 0, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 2413.9431770847045 atol=1E-6
     @test ci.upper    ≈ Inf
     @test ci.estimate ≈ Inf
 
     #-- mn2
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:or, method=:mn2)
+    ci = ClinicalTrialUtilities.orpropci(30, 100, 40, 90; alpha=0.05, method=:mn2)
     @test ci.lower    ≈ 0.2951669 atol=1E-6
     @test ci.upper    ≈ 0.9722965 atol=1E-6
     @test ci.estimate ≈ 0.5357142 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(100, 100, 90, 90; alpha=0.05, type=:or, method=:mn2)
+    ci = ClinicalTrialUtilities.orpropci(100, 100, 90, 90; alpha=0.05, method=:mn2)
     @test ci.lower    ≈ 0.0
     @test ci.upper    ≈ Inf
     #@test ci.estimate == NaN
 
-    ci = ClinicalTrialUtilities.twoprop(0, 100, 90, 90; alpha=0.05, type=:or, method=:mn2)
+    ci = ClinicalTrialUtilities.orpropci(0, 100, 90, 90; alpha=0.05,  method=:mn2)
     @test ci.lower    ≈ 0.0
     @test ci.upper    ≈ 0.0004144169697670039  atol=1E-6
     @test ci.estimate ≈ 0.0
 
-    ci = ClinicalTrialUtilities.twoprop(100, 100, 0, 90; alpha=0.05, type=:or, method=:mn2)
+    ci = ClinicalTrialUtilities.orpropci(100, 100, 0, 90; alpha=0.05,  method=:mn2)
     @test ci.lower    ≈ 2411.6137253788347 atol=1E-6
     @test ci.upper    ≈ Inf
     @test ci.estimate ≈ Inf
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:or, method=:awoolf)
+    ci = ClinicalTrialUtilities.orpropci(30, 100, 40, 90; alpha=0.05,  method=:awoolf)
     @test ci.lower    ≈ 0.2982066 atol=1E-6
     @test ci.upper    ≈ 0.9758363 atol=1E-6
     @test ci.estimate ≈ 0.5394449 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:or, method=:woolf)
+    ci = ClinicalTrialUtilities.orpropci(30, 100, 40, 90; alpha=0.05,  method=:woolf)
     @test ci.lower    ≈ 0.29504200273798975 atol=1E-6
     @test ci.upper    ≈ 0.9727082695179062 atol=1E-6
     @test ci.estimate ≈ 0.5357142857142857 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:or, method=:mover)
+    ci = ClinicalTrialUtilities.orpropci(30, 100, 40, 90; alpha=0.05, method=:mover)
     @test ci.lower    ≈ 0.2963748435372293 atol=1E-6
     @test ci.upper    ≈ 0.9689058534780502 atol=1E-6
     @test ci.estimate ≈ 0.5357142857142857 atol=1E-6
 
     #----
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:nhs)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05, method=:nhs)
     @test ci.lower    ≈ -0.275381800 atol=1E-6
     @test ci.upper    ≈ -0.007158419 atol=1E-6
     @test ci.estimate ≈ -0.1444444   atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:ac)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05, method=:ac)
     @test ci.lower    ≈ -0.276944506 atol=1E-6
     @test ci.upper    ≈ -0.006516705 atol=1E-6
     @test ci.estimate ≈ -0.1444444   atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:mn)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ -0.2781290897168457 atol=1E-6
     @test ci.upper    ≈ -0.006708341755865329 atol=1E-6
     @test ci.estimate ≈ -0.1444444   atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:mee)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05, method=:mee)
     @test ci.lower    ≈ -0.27778775409226936 atol=1E-6
     @test ci.upper    ≈ -0.007071205228197489 atol=1E-6
     @test ci.estimate ≈ -0.14444444444 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:mee2)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05,  method=:mee2)
     #Roots 0.7.4 CTU 0.1.7
     @test ci.lower    ≈ -0.27778778455 atol=1E-5 #Chang atol for validation
     @test ci.upper    ≈ -0.00707120778 atol=1E-5
     @test ci.estimate ≈ -0.14444444444 atol=1E-7
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:wald)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05, method=:wald)
     @test ci.lower    ≈ -0.28084842238 atol=1E-6
     @test ci.upper    ≈ -0.00804046650 atol=1E-6
     @test ci.estimate ≈ -0.14444444444 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:diff, method=:waldcc)
+    ci = ClinicalTrialUtilities.diffpropci(30, 100, 40, 90; alpha=0.05, method=:waldcc)
     @test ci.lower    ≈ -0.29140397794 atol=1E-6
     @test ci.upper    ≈  0.00251508905 atol=1E-6
     @test ci.estimate ≈ -0.14444444444 atol=1E-6
@@ -142,44 +142,44 @@ println(" ---------------------------------- ")
     #---- RR
     #-- mn
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:rr, method=:mn)
+    ci = ClinicalTrialUtilities.rrpropci(30, 100, 40, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 0.46636099123297575 atol=1E-6
     @test ci.upper    ≈ 0.9799258384796817 atol=1E-6
     @test ci.estimate ≈ 0.675 atol=1E-6
 
-    ci = ClinicalTrialUtilities.twoprop(100, 100, 90, 90; alpha=0.05, type=:rr, method=:mn)
+    ci = ClinicalTrialUtilities.rrpropci(100, 100, 90, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 0.0
     @test ci.upper    ≈ Inf
     #@test ci.estimate == NaN
 
-    ci = ClinicalTrialUtilities.twoprop(0, 100, 90, 90; alpha=0.05, type=:rr, method=:mn)
+    ci = ClinicalTrialUtilities.rrpropci(0, 100, 90, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 0.0
     @test ci.upper    ≈ 0.018137090385952483  atol=1E-6
     @test ci.estimate ≈ 0.0
 
-    ci = ClinicalTrialUtilities.twoprop(100, 100, 0, 90; alpha=0.05, type=:rr, method=:mn)
+    ci = ClinicalTrialUtilities.rrpropci(100, 100, 0, 90; alpha=0.05, method=:mn)
     @test ci.lower    ≈ 44.8498645475395 atol=1E-6
     @test ci.upper    ≈ Inf
     @test ci.estimate ≈ Inf
 
     #-- cli
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:rr, method=:cli)
+    ci = ClinicalTrialUtilities.rrpropci(30, 100, 40, 90; alpha=0.05, method=:cli)
     @test ci.lower    ≈ 0.4663950 atol=1E-6
     @test ci.upper    ≈ 0.9860541 atol=1E-6
     @test ci.estimate ≈ 0.675     atol=1E-4
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:rr, method=:mover)
+    ci = ClinicalTrialUtilities.rrpropci(30, 100, 40, 90; alpha=0.05, method=:mover)
     @test ci.lower    ≈ 0.4634443 atol=1E-6
     @test ci.upper    ≈ 0.9808807 atol=1E-6
     @test ci.estimate ≈ 0.675     atol=1E-4
 
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:rr, method=:mover)
+    ci = ClinicalTrialUtilities.rrpropci(30, 100, 40, 90; alpha=0.05, method=:mover)
     @test ci.lower    ≈ 0.4634443 atol=1E-6
     @test ci.upper    ≈ 0.9808807 atol=1E-6
     @test ci.estimate ≈ 0.675     atol=1E-4
     #katz
-    ci = ClinicalTrialUtilities.twoprop(30, 100, 40, 90; alpha=0.05, type=:rr, method=:katz)
+    ci = ClinicalTrialUtilities.rrpropci(30, 100, 40, 90; alpha=0.05, method=:katz)
     @test ci.lower    ≈ 0.4624671 atol=1E-6
     @test ci.upper    ≈ 0.9852050 atol=1E-6
     @test ci.estimate ≈ 0.675     atol=1E-4
diff --git a/test/ctsamplen.jl b/test/ctsamplen.jl
new file mode 100644
index 0000000..6072a15
--- /dev/null
+++ b/test/ctsamplen.jl
@@ -0,0 +1,152 @@
+@testset "#1  ctsamplen Test      " begin
+    #Sample Size Calculations in Clinical Research, Second Edition, Shein-Chung Chow, Ph.D., 2008, International Standard Book Number‑13: 978‑1‑58488‑982‑3
+    #1
+    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ea, group=:one, alpha=0.05, beta=0.2, sd=1, a=2, b=1.5)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 32
+    Base.show(io, t)
+    Base.show(io, t.task)
+    #2
+    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ei, group=:one, alpha=0.05, beta=0.2, sd=0.1, diff=0.05, a=2, b=2)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 35
+    Base.show(io, t)
+    #3
+    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ns, group=:one, alpha=0.05, beta=0.2, sd=1, diff=-0.5, a=2, b=1.5)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 7
+    Base.show(io, t)
+    #4
+    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ea, group=:two, alpha=0.05, beta=0.2, sd=10, a=5, b=10, k=1)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 63
+    Base.show(io, t)
+    #5
+    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ei, group=:two, alpha=0.05, beta=0.2, sd=10, diff=5, a=5, b=4, k=1)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 108
+    Base.show(io, t)
+    #6
+    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ns, group=:two, alpha=0.05, beta=0.2, sd=10, diff=5, a=5, b=5, k=1)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 50
+    Base.show(io, t)
+    #7
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ea, group=:one, alpha=0.05, beta=0.2, a=0.5, b=0.3)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 50
+    Base.show(io, t)
+    #8
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ei, group=:one, alpha=0.05, beta=0.2, diff=0.2, a=0.6, b=0.6)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 52
+    Base.show(io, t)
+    #9
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ns, group=:one, alpha=0.05, beta=0.2, diff=-0.1, a=0.5, b=0.3)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 18
+    Base.show(io, t)
+    #10    p.92
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ea, group=:two, alpha=0.05, beta=0.2, a=0.65, b=0.85)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 70
+    Base.show(io, t)
+    #11    p.93
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ei, group=:two, alpha=0.05, beta=0.2, diff=0.2, a=0.75, b=0.80)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 133
+    Base.show(io, t)
+    #12    p.92
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ns, group=:two, alpha=0.05, beta=0.2, diff=-0.1, a=0.85, b=0.65)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 25
+    Base.show(io, t)
+    #13    p.108
+    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ea,  alpha=0.05, beta=0.2, a=0.4, b=0.25)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 156
+    Base.show(io, t)
+    #14.1    p.109
+    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ei,  alpha=0.05, beta=0.2, diff=0.5, a=0.25, b=0.25)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 366
+    Base.show(io, t)
+    #15.1    p.108
+    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ns,  alpha=0.05, beta=0.2, diff=0.2, a=0.4, b=0.25)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 242
+    Base.show(io, t)
+    #14.2
+    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ei,  alpha=0.05, beta=0.2, diff=exp(0.5), a=0.25, b=0.25, logscale = false)
+    @test ceil(t.result) == 366
+    Base.show(io, t)
+    #15.2
+    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ns,  alpha=0.05, beta=0.2, diff=exp(0.2), a=0.4, b=0.25, logscale = false)
+    @test ceil(t.result) == 242
+    Base.show(io, t)
+    #16
+    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:mcnm, a=0.45, b=0.05)
+    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 23
+    Base.show(io, t)
+
+    #Additional
+    #Different type input
+    @test ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ns, group=:two, alpha=0.05, beta=0.2, diff=1, sd=20.0, a=1, b=2).result ≈ 1236.511446403953 atol=1E-12
+
+    @test ceil(ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ns, group=:two, alpha=0.05, beta=0.2, diff=0.05, a=0.85, b=0.65).result) == 98
+end
+
+println(" ---------------------------------- ")
+@testset "#2  ctpower Test        " begin
+
+    #1
+    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ea, group=:one, a=2, b=1.5, sd=1,n=32, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8074304194325561  atol=1E-7
+    Base.show(io, t)
+    Base.show(io, t.task)
+    #2
+    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ei, group=:one, a=2, b=2, sd=0.1, diff=0.05, n=35, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8108839754376387  atol=1E-7
+    Base.show(io, t)
+    #3
+    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ns, group=:one, a=2, b=1.5, sd=1, diff=-0.5, n=7, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8415707712023641  atol=1E-7
+    Base.show(io, t)
+    #4
+    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ea, group=:two, a=5, b=10, sd=10, n=63, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8013023941055788  atol=1E-7
+    Base.show(io, t)
+    #5
+    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ei, group=:two, a=5, b=4, sd=10, diff=5, n=108, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.80452354556060    atol=1E-7
+    Base.show(io, t)
+    #6
+    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ns, group=:two, a=5, b=5, sd=10, diff=5, n=50, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8037819415575257  atol=1E-7
+    Base.show(io, t)
+    #7
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ea, group=:one, a=0.5, b=0.3, n=50, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8074304194325561  atol=1E-7
+    Base.show(io, t)
+    #8
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ei, group=:one, a=0.6, b=0.6, diff=0.2, n=52, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8060834056011101  atol=1E-7
+    Base.show(io, t)
+    #9
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ns, group=:one, a=0.5, b=0.3, diff=-0.1, n=18, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8161481827204281  atol=1E-7
+    Base.show(io, t)
+    #10
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ea, group=:two, a=0.65, b=0.85, n=70, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8019139068528     atol=1E-7
+    Base.show(io, t)
+    #11
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ei, group=:two, a=0.65, b=0.85, diff=0.05, n=136, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8033294052407269  atol=1E-7
+    Base.show(io, t)
+    #12
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ns, group=:two, a=0.85, b=0.65, diff=-0.1, n=25, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.808599833380679   atol=1E-7
+    Base.show(io, t)
+    #13
+    t = ClinicalTrialUtilities.ctpower(param=:or, type=:ea, a=0.4, b=0.25, n=156, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8020239054864792  atol=1E-7
+    Base.show(io, t)
+    #14
+    t = ClinicalTrialUtilities.ctpower(param=:or, type=:ei, a=0.25, b=0.25, diff=0.5, n=366, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8008593380478983  atol=1E-7
+    Base.show(io, t)
+    #15
+    t = ClinicalTrialUtilities.ctpower(param=:or, type=:ns, a=0.4, b=0.25, diff=0.2, n=242, alpha=0.05)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8007200876001626  atol=1E-7
+    Base.show(io, t)
+    #16
+    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:mcnm, a=0.45, b=0.05, n=23, alpha=0.1)
+    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.9023805           atol=1E-7
+    Base.show(io, t)
+end
diff --git a/test/test.jl b/test/test.jl
index b279fae..61e6447 100644
--- a/test/test.jl
+++ b/test/test.jl
@@ -18,158 +18,7 @@ println(" ---------   START TEST   --------- ")
 println(" ---------------------------------- ")
 println(" ---------------------------------- ")
 
-@testset "#1  ctsamplen Test      " begin
-    #Sample Size Calculations in Clinical Research, Second Edition, Shein-Chung Chow, Ph.D., 2008, International Standard Book Number‑13: 978‑1‑58488‑982‑3
-    #1
-    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ea, group=:one, alpha=0.05, beta=0.2, sd=1, a=2, b=1.5)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 32
-    Base.show(io, t)
-    Base.show(io, t.task)
-    #2
-    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ei, group=:one, alpha=0.05, beta=0.2, sd=0.1, diff=0.05, a=2, b=2)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 35
-    Base.show(io, t)
-    #3
-    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ns, group=:one, alpha=0.05, beta=0.2, sd=1, diff=-0.5, a=2, b=1.5)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 7
-    Base.show(io, t)
-    #4
-    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ea, group=:two, alpha=0.05, beta=0.2, sd=10, a=5, b=10, k=1)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 63
-    Base.show(io, t)
-    #5
-    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ei, group=:two, alpha=0.05, beta=0.2, sd=10, diff=5, a=5, b=4, k=1)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 108
-    Base.show(io, t)
-    #6
-    t = ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ns, group=:two, alpha=0.05, beta=0.2, sd=10, diff=5, a=5, b=5, k=1)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 50
-    Base.show(io, t)
-    #7
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ea, group=:one, alpha=0.05, beta=0.2, a=0.5, b=0.3)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 50
-    Base.show(io, t)
-    #8
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ei, group=:one, alpha=0.05, beta=0.2, diff=0.2, a=0.6, b=0.6)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 52
-    Base.show(io, t)
-    #9
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ns, group=:one, alpha=0.05, beta=0.2, diff=-0.1, a=0.5, b=0.3)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 18
-    Base.show(io, t)
-    #10    p.92
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ea, group=:two, alpha=0.05, beta=0.2, a=0.65, b=0.85)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 70
-    Base.show(io, t)
-    #11    p.93
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ei, group=:two, alpha=0.05, beta=0.2, diff=0.2, a=0.75, b=0.80)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 133
-    Base.show(io, t)
-    #12    p.92
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ns, group=:two, alpha=0.05, beta=0.2, diff=-0.1, a=0.85, b=0.65)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 25
-    Base.show(io, t)
-    #13    p.108
-    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ea,  alpha=0.05, beta=0.2, a=0.4, b=0.25)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 156
-    Base.show(io, t)
-    #14.1    p.109
-    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ei,  alpha=0.05, beta=0.2, diff=0.5, a=0.25, b=0.25)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 366
-    Base.show(io, t)
-    #15.1    p.108
-    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ns,  alpha=0.05, beta=0.2, diff=0.2, a=0.4, b=0.25)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 242
-    Base.show(io, t)
-    #14.2
-    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ei,  alpha=0.05, beta=0.2, diff=exp(0.5), a=0.25, b=0.25, logscale = false)
-    @test ceil(t.result) == 366
-    Base.show(io, t)
-    #15.2
-    t = ClinicalTrialUtilities.ctsamplen(param=:or, type=:ns,  alpha=0.05, beta=0.2, diff=exp(0.2), a=0.4, b=0.25, logscale = false)
-    @test ceil(t.result) == 242
-    Base.show(io, t)
-    #16
-    t = ClinicalTrialUtilities.ctsamplen(param=:prop, type=:mcnm, a=0.45, b=0.05)
-    @test ceil(t.result) == ceil(ClinicalTrialUtilities.ctsamplen(t.task).result) == 23
-    Base.show(io, t)
-
-    #Additional
-    #Different type input
-    @test ClinicalTrialUtilities.ctsamplen(param=:mean, type=:ns, group=:two, alpha=0.05, beta=0.2, diff=1, sd=20.0, a=1, b=2).result ≈ 1236.511446403953 atol=1E-12
-
-    @test ceil(ClinicalTrialUtilities.ctsamplen(param=:prop, type=:ns, group=:two, alpha=0.05, beta=0.2, diff=0.05, a=0.85, b=0.65).result) == 98
-end
-
-println(" ---------------------------------- ")
-@testset "#2  ctpower Test        " begin
-
-    #1
-    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ea, group=:one, a=2, b=1.5, sd=1,n=32, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8074304194325561  atol=1E-7
-    Base.show(io, t)
-    Base.show(io, t.task)
-    #2
-    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ei, group=:one, a=2, b=2, sd=0.1, diff=0.05, n=35, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8108839754376387  atol=1E-7
-    Base.show(io, t)
-    #3
-    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ns, group=:one, a=2, b=1.5, sd=1, diff=-0.5, n=7, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8415707712023641  atol=1E-7
-    Base.show(io, t)
-    #4
-    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ea, group=:two, a=5, b=10, sd=10, n=63, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8013023941055788  atol=1E-7
-    Base.show(io, t)
-    #5
-    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ei, group=:two, a=5, b=4, sd=10, diff=5, n=108, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.80452354556060    atol=1E-7
-    Base.show(io, t)
-    #6
-    t = ClinicalTrialUtilities.ctpower(param=:mean, type=:ns, group=:two, a=5, b=5, sd=10, diff=5, n=50, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8037819415575257  atol=1E-7
-    Base.show(io, t)
-    #7
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ea, group=:one, a=0.5, b=0.3, n=50, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8074304194325561  atol=1E-7
-    Base.show(io, t)
-    #8
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ei, group=:one, a=0.6, b=0.6, diff=0.2, n=52, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8060834056011101  atol=1E-7
-    Base.show(io, t)
-    #9
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ns, group=:one, a=0.5, b=0.3, diff=-0.1, n=18, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8161481827204281  atol=1E-7
-    Base.show(io, t)
-    #10
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ea, group=:two, a=0.65, b=0.85, n=70, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8019139068528     atol=1E-7
-    Base.show(io, t)
-    #11
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ei, group=:two, a=0.65, b=0.85, diff=0.05, n=136, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8033294052407269  atol=1E-7
-    Base.show(io, t)
-    #12
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:ns, group=:two, a=0.85, b=0.65, diff=-0.1, n=25, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.808599833380679   atol=1E-7
-    Base.show(io, t)
-    #13
-    t = ClinicalTrialUtilities.ctpower(param=:or, type=:ea, a=0.4, b=0.25, n=156, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8020239054864792  atol=1E-7
-    Base.show(io, t)
-    #14
-    t = ClinicalTrialUtilities.ctpower(param=:or, type=:ei, a=0.25, b=0.25, diff=0.5, n=366, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8008593380478983  atol=1E-7
-    Base.show(io, t)
-    #15
-    t = ClinicalTrialUtilities.ctpower(param=:or, type=:ns, a=0.4, b=0.25, diff=0.2, n=242, alpha=0.05)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.8007200876001626  atol=1E-7
-    Base.show(io, t)
-    #16
-    t = ClinicalTrialUtilities.ctpower(param=:prop, type=:mcnm, a=0.45, b=0.05, n=23, alpha=0.1)
-    @test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.9023805           atol=1E-7
-    Base.show(io, t)
-end
+include("ctsamplen.jl")
 
 println(" ---------------------------------- ")
 @testset "#3  besamplen Test      " begin
@@ -335,36 +184,7 @@ println(" ---------------------------------- ")
     #@test ClinicalTrialUtilities.ctpower(t.task).result ≈ 0.0001785665  atol=1E-10
 end
 
-println(" ---------------------------------- ")
-@testset "#5  utils Test          " begin
-
-@testset "  ci2cv Test            " begin
-    cvms = ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30, design=:d2x2x4, cvms=true)
-    @test cvms[1] ≈ 0.583175066140736 && cvms[2] ≈ 0.29273913226894244
-    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30, design=:d2x2x4, mso=true) ≈ 0.29273913226894244
-    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30) ≈ 0.387417014838382
-    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.8, theta2 = 1.25, n=30) ≈ 0.5426467811605913
-    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 1.01, theta2 = 1.21, n=31, design=:d2x2) ≈ 0.21151405971696524
-end
-
-@testset "  pooledcv            " begin
-    data = DataFrame(cv = Float64[], df = Int[])
-    push!(data, (0.12, 12))
-    push!(data, (0.2, 20))
-    push!(data, (0.25, 30))
-    ci = ClinicalTrialUtilities.pooledcv(data; cv="cv", df="df")
-    @test ci.lower    ≈ 0.18145259424967664 atol=1E-15
-    @test ci.upper    ≈ 0.2609307413637307 atol=1E-15
-    @test ci.estimate ≈ 0.21393949168210136 atol=1E-15
-    ci = ClinicalTrialUtilities.pooledcv(data; cv="cv", df="df", returncv=false)
-    @test ci.lower    ≈ 0.032394625994562894 atol=1E-15
-    @test ci.upper    ≈ 0.06586718662236608 atol=1E-15
-    @test ci.estimate ≈ 0.04475355764465427 atol=1E-15
-end
-
-@test ClinicalTrialUtilities.cvfromsd(ClinicalTrialUtilities.sdfromcv(0.2)) ≈ 0.2
-@test ClinicalTrialUtilities.cvfromvar(ClinicalTrialUtilities.varfromcv(0.2)) ≈ 0.2
-end
+include("utils.jl")
 
 println(" ---------------------------------- ")
 @testset "Internal functions test " begin
@@ -498,6 +318,7 @@ println(" ---------------------------------- ")
     pk   = ClinicalTrialUtilities.nca!(pkds)
     df   = ClinicalTrialUtilities.DataFrame(pk; unst = true)
     ClinicalTrialUtilities.htmlexport(df; io = io, sort = :Subject, rspan=:all, title = "PK Parameters", dict = :pk)
+    @test true
 end
 
 println(" ---------------------------------- ")
diff --git a/test/utils.jl b/test/utils.jl
new file mode 100644
index 0000000..0a9140a
--- /dev/null
+++ b/test/utils.jl
@@ -0,0 +1,44 @@
+println(" ---------------------------------- ")
+@testset "#5  utils Test          " begin
+
+@testset "  ci2cv Test            " begin
+    cvms = ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30, design=:d2x2x4, cvms=true)
+    @test cvms[1] ≈ 0.583175066140736 && cvms[2] ≈ 0.29273913226894244
+    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30, design=:d2x2x4, mso=true) ≈ 0.29273913226894244
+    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30) ≈ 0.387417014838382
+    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 0.8, theta2 = 1.25, n=30) ≈ 0.5426467811605913
+    @test ClinicalTrialUtilities.cvfromci(;alpha = 0.05, theta1 = 1.01, theta2 = 1.21, n=31, design=:d2x2) ≈ 0.21151405971696524
+
+    @test ClinicalTrialUtilities.cvfromci(0.9, 1.25, 30) ≈ 0.387417014838382
+end
+
+@testset "  pooledcv            " begin
+    data = DataFrame(cv = Float64[], df = Int[])
+    push!(data, (0.12, 12))
+    push!(data, (0.2, 20))
+    push!(data, (0.25, 30))
+    ci = ClinicalTrialUtilities.pooledcv(data; cv="cv", df="df")
+    @test ci.lower    ≈ 0.18145259424967664 atol=1E-15
+    @test ci.upper    ≈ 0.2609307413637307 atol=1E-15
+    @test ci.estimate ≈ 0.21393949168210136 atol=1E-15
+
+    ci = ClinicalTrialUtilities.pooledcv(data; cv="cv", df="df", returncv=false)
+    @test ci.lower    ≈ 0.032394625994562894 atol=1E-15
+    @test ci.upper    ≈ 0.06586718662236608 atol=1E-15
+    @test ci.estimate ≈ 0.04475355764465427 atol=1E-15
+
+    ci = ClinicalTrialUtilities.pooledcv([0.12, 0.2, 0.25], [12, 20, 30])
+    @test ci.lower    ≈ 0.18145259424967664 atol=1E-15
+    @test ci.upper    ≈ 0.2609307413637307 atol=1E-15
+    @test ci.estimate ≈ 0.21393949168210136 atol=1E-15
+
+    ci = ClinicalTrialUtilities.pooledcv([0.12, 0.2, 0.25], [14, 22, 32], [:d2x2, :d2x2, :d2x2])
+    @test ci.lower    ≈ 0.18145259424967664 atol=1E-15
+    @test ci.upper    ≈ 0.2609307413637307 atol=1E-15
+    @test ci.estimate ≈ 0.21393949168210136 atol=1E-15
+end
+
+@test ClinicalTrialUtilities.cvfromsd(ClinicalTrialUtilities.sdfromcv(0.2)) ≈ 0.2
+
+@test ClinicalTrialUtilities.cvfromvar(ClinicalTrialUtilities.varfromcv(0.2)) ≈ 0.2
+end