Merge pull request #49 from PharmCat/dev

v0.3.2
  - bugfix fisher test
  - add show
  - propci for ConTab
  - bump dependencies

Project.toml

@@ -1,7 +1,7 @@
 authors = ["Vladimir Arnautov ([email protected])"]
 name = "ClinicalTrialUtilities"
 uuid = "535c2557-d7d0-564d-8ff9-4ae146c18cfe"
-version = "0.3.1"
+version = "0.3.2"
 
 [deps]
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
@@ -13,7 +13,6 @@ Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 
 [extras]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
@@ -24,13 +23,12 @@ Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 test = ["CSV", "Test", "Plots"]
 
 [compat]
-julia = "1.0, 1.1, 1.2, 1.3, 1.4"
-Distributions = "0.16, 0.17, 0.18, 0.19, 0.20, 0.21, 0.22, 0.23"
+julia = "1.0, 1.1, 1.2, 1.3, 1.4, 1.5"
+Distributions = "0.16, 0.17, 0.18, 0.19, 0.20, 0.21, 0.22, 0.23, 0.24"
 StatsBase = "0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.30, 0.31, 0.32, 0.33"
 QuadGK = "2.0, 2.1, 2.2, 2.3, 2.4"
-SpecialFunctions = "0.8, 0.9, 0.10"
-Roots = "0.7, 0.8, 1.0"
-RecipesBase = "0.7, 0.8, 1.0"
+SpecialFunctions = "0.8, 0.9, 0.10, 1"
+Roots = "0.7, 0.8, 1"
+RecipesBase = "0.7, 0.8, 1"
 Reexport = "0.1, 0.2"
 DataFrames = "0.19, 0.20"
-CSV = "0.5, 0.6"

README.md

@@ -8,10 +8,6 @@
 [![Coverage Status](https://coveralls.io/repos/github/PharmCat/ClinicalTrialUtilities.jl/badge.svg?branch=master)](https://coveralls.io/github/PharmCat/ClinicalTrialUtilities.jl?branch=master)
 [![Latest docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://pharmcat.github.io/ClinicalTrialUtilities.jl/dev/)
 
-## Difference since v0.3.0
-
-  Wrong Equivalence Hypothesis alpha level! Use 0.2.7 or 0.3.1 version.
-
 ## Description
 
 The package is designed to perform calculations related to the planning and analysis of the results of clinical trials. The package includes the basic functions described below, as well as a few modules to perform specific calculations.

cange.log

@@ -1,3 +1,9 @@
+v0.3.2
+  - bugfix fisher test
+  - add show
+  - propci for ConTab
+  - bump dependencies
+
 v0.3.1
 
   - deleteat! fix

docs/src/index.md

@@ -29,6 +29,10 @@ When ctpower/ctsamplen used:
 - :ei - Equivalencens: two one-sided hypothesis;
 - :ns - Non-Inferiority / Superiority: one-sided hypothesis, for some cases you should use two-sided hypothesis for  Non-Inferiority/Superiority, you can use alpha/2 for this;
 
+## Invalidated version v0.3.0 (removed from release page)
+
+  Wrong Equivalence Hypothesis alpha level! Use 0.2.7, 0.3.1 version or higher.
+
 ## Contents
 
 ```@contents

src/ci.jl

@@ -154,6 +154,17 @@ function propci(x::Int, n::Int; alpha::Real = 0.05, method = :default)::ConfInt
         throw(ArgumentError("unknown method!"))
     end
 end
+"""
+    propci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)
+
+Confidence interval for proportions a / (a + b) and c / (c + d)
+"""
+function propci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)
+    d = Dict()
+    d[tab.row[1]] = propci(tab.a, tab.a + tab.b; alpha = alpha, method = method)
+    d[tab.row[2]] = propci(tab.c, tab.c + tab.d; alpha = alpha, method = method)
+    d
+end
 """
     diffpropci(x1::Int, n1::Int, x2::Int, n2::Int;
         alpha::Real = 0.05, method::Symbol = :default)::ConfInt
@@ -162,18 +173,33 @@ Confidence interval for proportion difference.
 
 # Computation methods:
 
-- :nhs - Newcombes Hybrid (wilson) Score interval for the difference of proportions;
-- :nhscc - Newcombes Hybrid Score CC;
-- :ac - Agresti-Caffo interval for the difference of proportions;
-- :mn | :default - Method of Mee 1984 with Miettinen and Nurminen modification;
-- :mee | :fm - Mee maximum likelihood method;
-- :wald - Wald CI without CC;
-- :waldcc - Wald CI with CC;
+- `:nhs` - Newcombes Hybrid (wilson) Score interval for the difference of proportions;
+- `:nhscc` - Newcombes Hybrid Score CC;
+- `:ac` - Agresti-Caffo interval for the difference of proportions;
+- `:mn` | `:default` - Method of Mee 1984 with Miettinen and Nurminen modification;
+- `:mee` | `:fm` - Mee maximum likelihood method;
+- `:wald` - Wald CI without CC;
+- `:waldcc` - Wald CI with CC;
+
+# References
+
+  * nhs, nhscc - Newcombe RG (1998), Interval Estimation for the Difference Between Independent Proportions: Comparison of Eleven Methods. Statistics in Medicine 17, 873-890.
+  * ac - Agresti A, Caffo B., “Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures”, American Statistician 54: 280–288 (2000)
+  * mn - Miettinen, O. and Nurminen, M. (1985), Comparative analysis of two rates. Statist. Med., 4: 213-226. doi:10.1002/sim.4780040211
+  * mee - Mee RW (1984) Confidence bounds for the difference between two probabilities, Biometrics40:1175-1176
+  * Brown, L.D., Cai, T.T., and DasGupta, A. Interval estimation for a binomial proportion.
+    Statistical Science, 16(2):101–117, 2001.
+  * Farrington, C. P. and Manning, G. (1990), “Test Statistics and Sample Size Formulae for Comparative Binomial Trials with Null Hypothesis of Non-zero Risk Difference or Non-unity Relative Risk,” Statistics in Medicine, 9, 1447–1454
+  * Li HQ, Tang ML, Wong WK. Confidence intervals for ratio of two Poisson rates using the methodof variance estimates recovery. Computational Statistics 2014; 29(3-4):869-889
+  * Brown, L., Cai, T., & DasGupta, A. (2003). INTERVAL ESTIMATION IN EXPONENTIAL FAMILIES. Statistica Sinica, 13(1), 19-49.
 """
 function diffpropci(x1::Int, n1::Int, x2::Int, n2::Int; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
     if alpha >= 1.0 || alpha <= 0.0
         throw(ArgumentError("Alpha shold be > 0.0 and < 1.0"))
     end
+    if x1 > n1 || x2 > n2
+        throw(ArgumentError("X cann't be more than N"))
+    end
     if method == :nhs
         return propdiffnhsci(x1, n1, x2, n2, alpha)
     elseif method == :nhscc
@@ -194,7 +220,11 @@ function diffpropci(x1::Int, n1::Int, x2::Int, n2::Int; alpha::Real = 0.05, meth
         throw(ArgumentError("Method unknown!"))
     end
 end
-#TEST
+"""
+    diffpropci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
+
+Confidence interval for proportion difference: (a / (a + b)) - (c / (c + d))
+"""
 function diffpropci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
     diffpropci(tab.a, tab.a + tab.b, tab.c, tab.c + tab.d; alpha = alpha, method = method)
 end
@@ -226,6 +256,14 @@ function rrpropci(x1::Int, n1::Int, x2::Int, n2::Int; alpha::Real = 0.05, method
         throw(ArgumentError("Method unknown!"))
     end
 end
+"""
+    rrpropci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
+
+Confidence interval for relative risk.
+"""
+function rrpropci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
+    rrpropci(tab.a, tab.a + tab.b, tab.c, tab.c + tab.d; alpha = alpha, method = method)
+end
 """
     orpropci(x1::Int, n1::Int, x2::Int, n2::Int; alpha::Real = 0.05,
         method::Symbol = :default)::ConfInt
@@ -256,6 +294,14 @@ function orpropci(x1::Int, n1::Int, x2::Int, n2::Int; alpha::Real = 0.05, method
         throw(ArgumentError("Method unknown!"))
     end
 end
+"""
+    orpropci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
+
+Confidence interval for odd ratio.
+"""
+function orpropci(tab::ConTab{2,2}; alpha::Real = 0.05, method::Symbol = :default)::ConfInt
+    orpropci(tab.a, tab.a + tab.b, tab.c, tab.c + tab.d; alpha = alpha, method = method)
+end
 """
     meanci(m::Real, σ²::Real, n::Int; alpha::Real = 0.05,
         method=:default)::ConfInt

src/freque.jl

@@ -59,7 +59,7 @@ function Base.getproperty(obj::ConTab{2, 2}, attr::Symbol)
     elseif attr == :d
         return getfield(obj, :tab)[2,2]
     else
-        error("No field!")
+        return getfield(obj, attr)
     end
 end
 
@@ -129,7 +129,16 @@ function contab(data::DataFrame, sort; row::Symbol, col::Symbol)
     end
     return DataSet(result)
 end
+"""
+    contab(m; row = nothing, col = nothing)
 
+Make contingency table.
+"""
+function contab(m::Matrix; row = nothing, col = nothing)
+    if isa(row, Nothing) row = Vector{Symbol}(undef, size(m, 1)) .= Symbol("") end
+    if isa(col, Nothing) col = Vector{Symbol}(undef, size(m, 2)) .= Symbol("") end
+    ConTab(m, row, col)
+end
 """
     mcnmcontab
 """
@@ -178,7 +187,7 @@ function pirson(a::Matrix{Int})
     tm  = sum(a, dims=1)[1,:]
     tn  = sum(a, dims=2)[:,1]
     num = sum(tm)
-    ae  = Array{Real, 2}(undef, n, m)
+    ae  = Array{Float64, 2}(undef, n, m)
     for im = 1:m
         for in = 1:n
             ae[in, im] = tn[in]*tm[im]/num
@@ -199,7 +208,10 @@ end
 
 function fisher(a::Matrix{Int})
     dist  = Hypergeometric(sum(a[1, :]), sum(a[2, :]), sum(a[:, 1]))
-    value = min(2 * min(cdf(dist, a[1, 1]), ccdf(dist, a[1, 1])), 1.0)
+    l = cdf(dist, a[1, 1])
+    r = ccdf(dist, a[1, 1]-1)
+    value = min(2 * min(r, l), 1.0)
+    value, l, r
 end
 function fisher(t::ConTab{2, 2})
     fisher(t.tab)

src/show.jl

@@ -249,6 +249,24 @@ function Base.show(io::IO, obj::ConfInt)
         print(io, "Estimate: $(obj.estimate) ($(obj.lower) - $(obj.upper))")
 end
 
+#-------------------------------------------------------------------------------
+# Frequences
+function Base.show(io::IO, ct::ConTab{2, 2})
+        mx = Matrix{Any}(undef, 3, 3)
+        mx[2:3, 2:3] .= ct.tab
+        mx[2:3, 1] .= ct.row
+        mx[1, 2:3] .= ct.col
+        mx[1,1] = ""
+        println(io, "Contingency table 2X2")
+        println(io, "---------------------")
+        printmatrix(io, mx)
+        println(io, "---------------------")
+        if length(ct.sort) > 0
+                println(io, ct.sort)
+        end
+end
+
+
 #-------------------------------------------------------------------------------
 # OUTPUT
 function addspace(s::String, n::Int; first = false)::String

test/freque.jl

@@ -7,6 +7,10 @@ println(" ---------------------------------- ")
     frtab =  ClinicalTrialUtilities.freque(df; vars=:row, alpha = 0.05)
     @test frtab[1,2] == 17
 
+    @test ClinicalTrialUtilities.fisher(ClinicalTrialUtilities.ConTab([12 23; 22 33]))[2] ≈ 0.3752579856319276
+
+    @test ClinicalTrialUtilities.pirson(ClinicalTrialUtilities.ConTab([12 23; 22 33]))[4] ≈ 0.5856943077831229
+
 
     ctds = ClinicalTrialUtilities.contab(metadf, [:trial]; row = :group, col = :result)
     cmht = ClinicalTrialUtilities.metaprop(ctds, type = :or, model = :fixed, zeroadj = 0.0, tau = :ho)

test/test.jl

@@ -326,10 +326,6 @@ println(" ---------------------------------- ")
 
     @test  ClinicalTrialUtilities.diffmcnmwaldccci(10, 20, 11, 15; alpha = 0.05).lower ≈ -0.04741054890998043
 
-    @test ClinicalTrialUtilities.fisher(ClinicalTrialUtilities.ConTab([12 23; 22 33])) ≈ 0.7505159712638552
-
-    @test ClinicalTrialUtilities.pirson(ClinicalTrialUtilities.ConTab([12 23; 22 33]))[4] ≈ 0.5856943077831229
-
     @test  ClinicalTrialUtilities.mcnmtest(ClinicalTrialUtilities.McnmConTab([12 23; 22 33]); cc = false) ≈ 0.022222222222222223
 
     #= /*SAS Tesing code*/