diff --git a/src/analysis/sensitivity.jl b/src/analysis/sensitivity.jl
index 038da0b55..db6c96788 100644
--- a/src/analysis/sensitivity.jl
+++ b/src/analysis/sensitivity.jl
@@ -71,8 +71,8 @@ Get quantile value for a given categorical variable.
 - `factor_name` : Contains true where the factor is categorical and false otherwise
 - `steps` : Number of steps for defining bins
 """
-function _get_cat_quantile(foi_spec::DataFrame, factor_name::Symbol, steps::Vector{Float64})
-    fact_idx = foi_spec.fieldname .== factor_name
+function _get_cat_quantile(foi_spec::DataFrame, factor_name::Symbol, steps::Vector{Float64})::Vector{Float64}
+    fact_idx::BitVector = foi_spec.fieldname .== factor_name
     lb = foi_spec.lower_bound[fact_idx][1]
     ub = foi_spec.upper_bound[fact_idx][1]
 
@@ -392,7 +392,8 @@ function tsa(rs::ResultSet, y::AbstractMatrix{<:Real})::NamedDimsArray
 end
 
 """
-    rsa(X::DataFrame, y::Vector{<:Real}, model_spec::DataFrame; S=10)::NamedDimsArray
+    rsa(X::DataFrame, y::Vector{<:Real}, model_spec::DataFrame; S::Int64=10)::NamedDimsArray
+    rsa(rs::ResultSet, y::AbstractVector{<:Real}, factors::Vector{Symbol}; S::Int64=10)::NamedDimsArray
     rsa(rs::ResultSet, y::AbstractArray{<:Real}; S::Int64=10)::NamedDimsArray
 
 Perform Regional Sensitivity Analysis.
@@ -424,6 +425,7 @@ Note: Values of type `missing` indicate a lack of samples in the region.
 - `X` : scenario specification
 - `y` : scenario outcomes
 - `model_spec` : Model specification, as extracted by `ADRIA.model_spec(domain)` or from a `ResultSet`
+- `factors` : Specific model factors to examine
 - `S` : number of bins to slice factor space into (default: 10)
 
 # Returns
@@ -454,7 +456,7 @@ function rsa(
 )::NamedDimsArray
     N, D = size(X)
 
-    X_di = @MVector zeros(N)
+    X_di = zeros(N)
     sel = trues(N)
     factors = Symbol.(names(X))
 
@@ -465,7 +467,7 @@ function rsa(
         S = _category_bins(S, foi_spec[is_cat, :])
     end
 
-    X_q = @MVector zeros(S + 1)
+    X_q = zeros(S + 1)
     r_s = zeros(Union{Missing,Float64}, S, D)
     seq = collect(0.0:(1 / S):1.0)
 
@@ -508,7 +510,17 @@ end
 function rsa(
     rs::ResultSet, y::AbstractVector{<:Real}; S::Int64=10
 )::NamedDimsArray
-    return rsa(rs.inputs[:, Not(:RCP)], vec(y), rs.model_spec; S=S)
+    return rsa(rs.inputs[!, Not(:RCP)], y, rs.model_spec; S=S)
+end
+function rsa(
+    rs::ResultSet, y::AbstractVector{<:Real}, factors::Vector{Symbol}; S::Int64=10
+)::NamedDimsArray
+    return rsa(
+        rs.inputs[!, Not(:RCP)][!, factors],
+        y,
+        rs.model_spec[rs.model_spec.fieldname .∈ [factors], :];
+        S=S
+    )
 end