diff --git a/src/sampling.jl b/src/sampling.jl
index a256dd0c..de0d37f0 100644
--- a/src/sampling.jl
+++ b/src/sampling.jl
@@ -603,6 +603,9 @@ sample(wv::AbstractWeights) = sample(default_rng(), wv)
 sample(rng::AbstractRNG, a::AbstractArray, wv::AbstractWeights) = a[sample(rng, wv)]
 sample(a::AbstractArray, wv::AbstractWeights) = sample(default_rng(), a, wv)
 
+# Specialization for `UnitWeights`
+sample(rng::AbstractRNG, wv::UnitWeights) = rand(rng, 1:length(wv))
+
 """
     direct_sample!([rng], a::AbstractArray, wv::AbstractWeights, x::AbstractArray)
 
@@ -633,6 +636,14 @@ end
 direct_sample!(a::AbstractArray, wv::AbstractWeights, x::AbstractArray) =
     direct_sample!(default_rng(), a, wv, x)
 
+# Specialization for `UnitWeights`
+function direct_sample!(rng::AbstractRNG, a::AbstractArray, wv::UnitWeights, x::AbstractArray)
+    if length(a) != length(wv)
+        throw(DimensionMismatch(lazy"Number of samples ($(length(a))) and sample weights ($(length(wv))) must be equal."))
+    end
+    return direct_sample!(rng, a, x)
+end
+
 """
     alias_sample!([rng], a::AbstractArray, wv::AbstractWeights, x::AbstractArray)
 
@@ -741,7 +752,7 @@ function efraimidis_a_wsample_norep!(rng::AbstractRNG, a::AbstractArray,
     # calculate keys for all items
     keys = randexp(rng, n)
     for i in 1:n
-        @inbounds keys[i] = wv.values[i]/keys[i]
+        @inbounds keys[i] = wv[i]/keys[i]
     end
 
     # return items with largest keys
@@ -787,7 +798,7 @@ function efraimidis_ares_wsample_norep!(rng::AbstractRNG, a::AbstractArray,
     s = 0
     @inbounds for _s in 1:n
         s = _s
-        w = wv.values[s]
+        w = wv[s]
         w < 0 && error("Negative weight found in weight vector at index $s")
         if w > 0
             i += 1
@@ -802,7 +813,7 @@ function efraimidis_ares_wsample_norep!(rng::AbstractRNG, a::AbstractArray,
     @inbounds threshold = pq[1].first
 
     @inbounds for i in s+1:n
-        w = wv.values[i]
+        w = wv[i]
         w < 0 && error("Negative weight found in weight vector at index $i")
         w > 0 || continue
         key = w/randexp(rng)
@@ -861,7 +872,7 @@ function efraimidis_aexpj_wsample_norep!(rng::AbstractRNG, a::AbstractArray,
     s = 0
     @inbounds for _s in 1:n
         s = _s
-        w = wv.values[s]
+        w = wv[s]
         w < 0 && error("Negative weight found in weight vector at index $s")
         if w > 0
             i += 1
@@ -877,7 +888,7 @@ function efraimidis_aexpj_wsample_norep!(rng::AbstractRNG, a::AbstractArray,
     X = threshold*randexp(rng)
 
     @inbounds for i in s+1:n
-        w = wv.values[i]
+        w = wv[i]
         w < 0 && error("Negative weight found in weight vector at index $i")
         w > 0 || continue
         X -= w
@@ -958,6 +969,14 @@ sample(a::AbstractArray, wv::AbstractWeights, dims::Dims;
        replace::Bool=true, ordered::Bool=false) =
     sample(default_rng(), a, wv, dims; replace=replace, ordered=ordered)
 
+# Specialization for `UnitWeights`
+function sample!(rng::AbstractRNG, a::AbstractArray, wv::UnitWeights, x::AbstractArray; replace::Bool=true, ordered::Bool=false)
+    if length(a) != length(wv)
+        throw(DimensionMismatch(lazy"Number of samples ($(length(a))) and sample weights ($(length(wv))) must be equal."))
+    end
+    return sample!(rng, a, x; replace, ordered)
+end
+
 # wsample interface
 
 """
diff --git a/test/sampling.jl b/test/sampling.jl
index cd2ff096..a0d9bd51 100644
--- a/test/sampling.jl
+++ b/test/sampling.jl
@@ -297,3 +297,51 @@ end
         end
     end
 end
+
+# Custom unit weights without `values` field
+struct YAUnitWeights <: StatsBase.AbstractWeights{Int, Int, Vector{Int}}
+    n::Int
+end
+Base.sum(wv::YAUnitWeights) = wv.n
+Base.length(wv::YAUnitWeights) = wv.n
+Base.isempty(wv::YAUnitWeights) = iszero(wv.n)
+Base.size(wv::YAUnitWeights) = (wv.n,)
+Base.axes(wv::YAUnitWeights) = (Base.OneTo(wv.n),)
+function Base.getindex(wv::YAUnitWeights, i::Int)
+    @boundscheck checkbounds(wv, i)
+    return 1
+end
+
+@testset "issue #950" begin
+    # Sampling with unit weights behaves the same as sampling without weights
+    Random.seed!(123)
+    xs = sample(1:100, uweights(100), 10; replace=false)
+    Random.seed!(123)
+    @test xs == sample(1:100, 10; replace=false)
+
+    Random.seed!(123)
+    x = sample(uweights(100))
+    Random.seed!(123)
+    @test x == sample(1:100)
+
+    Random.seed!(123)
+    xs = direct_sample!(1:100, uweights(100), Vector{Int}(undef, 10))
+    Random.seed!(123)
+    @test xs == direct_sample!(1:100, Vector{Int}(undef, 10))
+
+    # Errors
+    @test_throws DimensionMismatch("Number of samples (100) and sample weights (99) must be equal.") sample(1:100, uweights(99), 10; replace=false)
+    @test_throws DimensionMismatch("Number of samples (80) and sample weights (53) must be equal.") direct_sample!(1:80, uweights(53), Vector{Int}(undef, 10))
+
+    # Custom units don't error and behave the same as sampling with `Weights`
+    Random.seed!(123)
+    xs = sample(1:100, YAUnitWeights(100), 10; replace=false)
+    Random.seed!(123)
+    @test xs == sample(1:100, weights(ones(Int, 100)), 10; replace=false)
+    for f in (StatsBase.efraimidis_a_wsample_norep!, StatsBase.efraimidis_ares_wsample_norep!, StatsBase.efraimidis_aexpj_wsample_norep!)
+        Random.seed!(123)
+        xs = f(1:100, YAUnitWeights(100), Vector{Int}(undef, 10))
+        Random.seed!(123)
+        @test xs == f(1:100, weights(ones(Int, 100)), Vector{Int}(undef, 10))
+    end
+end