diff --git a/src/univariate/continuous/logitnormal.jl b/src/univariate/continuous/logitnormal.jl
index 7fd5fb911..80e296c8b 100644
--- a/src/univariate/continuous/logitnormal.jl
+++ b/src/univariate/continuous/logitnormal.jl
@@ -72,6 +72,9 @@ LogitNormal(μ::Real=0.0) = LogitNormal(μ, one(μ); check_args=false)
 @distr_support LogitNormal 0.0 1.0
 #insupport(d::Union{D,Type{D}},x::Real) where {D<:LogitNormal} = 0.0 < x < 1.0
 
+# # TODO change @distr_support to generate functions that respect the type parameter
+# minimum(::LogitNormal{T}) where T = T(0)
+# maximum(::LogitNormal{T}) where T = T(1)
 
 #### Conversions
 convert(::Type{LogitNormal{T}}, μ::S, σ::S) where
diff --git a/src/univariate/locationscale.jl b/src/univariate/locationscale.jl
index 97e47d6f7..54ba2d319 100644
--- a/src/univariate/locationscale.jl
+++ b/src/univariate/locationscale.jl
@@ -49,12 +49,19 @@ struct AffineDistribution{T<:Real, S<:ValueSupport, D<:UnivariateDistribution{S}
     end
 end
 
-function AffineDistribution(μ::T, σ::T, ρ::UnivariateDistribution; check_args::Bool=true) where {T<:Real}
+function AffineDistribution(μ::T, σ::T, ρ::UnivariateDistribution, _T::Type; check_args::Bool=true) where {T<:Real}
+    #workaround ##1765 to allow specifying Float32 as parametric type
     @check_args AffineDistribution (σ, !iszero(σ))
-    _T = promote_type(eltype(ρ), T)
     return AffineDistribution{_T}(_T(μ), _T(σ), ρ)
 end
 
+function AffineDistribution(μ::T, σ::T, ρ::UnivariateDistribution; check_args::Bool=true) where {T<:Real}
+    #@check_args AffineDistribution (σ, !iszero(σ)) 
+    _T = promote_type(eltype(ρ), T)
+    #_T = promote_type(partype(ρ), T) breakes DiscreteNonParametric
+    return AffineDistribution(μ, σ, ρ, _T)
+end
+
 function AffineDistribution(μ::Real, σ::Real, ρ::UnivariateDistribution; check_args::Bool=true)
     return AffineDistribution(promote(μ, σ)..., ρ; check_args=check_args)
 end
@@ -62,7 +69,9 @@ end
 # aliases
 const LocationScale{T,S,D} = AffineDistribution{T,S,D}
 function LocationScale(μ::Real, σ::Real, ρ::UnivariateDistribution; check_args::Bool=true)
-    Base.depwarn("`LocationScale` is deprecated. Use `+` and `*` instead", :LocationScale)
+    Base.depwarn(
+        "`LocationScale` is deprecated. Use `+` and `*` instead " * 
+        "(see ?Distributions.AffineDistribution)", :LocationScale)
     # preparation for future PR where I remove σ > 0 check
     @check_args LocationScale (σ, σ > zero(σ))
     return AffineDistribution(μ, σ, ρ; check_args=false)
diff --git a/test/univariate/locationscale.jl b/test/univariate/locationscale.jl
index 761ce55bb..f7ac5b6c6 100644
--- a/test/univariate/locationscale.jl
+++ b/test/univariate/locationscale.jl
@@ -170,3 +170,13 @@ end
     @test ls_norm isa LocationScale{Float64, Continuous, Normal{Float64}}
     @test ls_norm isa Distributions.AffineDistribution{Float64, Continuous, Normal{Float64}}
 end
+
+
+@testset "user specified type Float32" begin
+    dln = LogitNormal(0f0, sqrt(2f0))
+    lower, upper = 1f0, 3f0
+    d = Distributions.AffineDistribution(lower, (upper -lower), dln, partype(dln))
+    @test scale(d) isa Float32
+    #@test minimum(d) isa Float32 # minimum is more complicated
+    #plot(d)
+end;
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