diff --git a/Project.toml b/Project.toml
index ea73e8f5..ee61bdac 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "GLM"
 uuid = "38e38edf-8417-5370-95a0-9cbb8c7f171a"
-version = "1.6.0"
+version = "1.6.1"
 
 [deps]
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
diff --git a/src/GLM.jl b/src/GLM.jl
index 768d9613..3f7d10b3 100644
--- a/src/GLM.jl
+++ b/src/GLM.jl
@@ -18,7 +18,7 @@ module GLM
     import StatsModels: hasintercept
     export coef, coeftable, confint, deviance, nulldeviance, dof, dof_residual,
            loglikelihood, nullloglikelihood, nobs, stderror, vcov, residuals, predict,
-           fitted, fit, fit!, model_response, response, modelmatrix, r2, r², adjr2, adjr², 
+           fitted, fit, fit!, model_response, response, modelmatrix, r2, r², adjr2, adjr²,
            cooksdistance, hasintercept
 
     export
@@ -81,6 +81,12 @@ module GLM
     abstract type DensePred <: LinPred end            # linear predictor with dense X
     abstract type LinPredModel <: RegressionModel end # model based on a linear predictor
 
+    @static if VERSION < v"1.8.0-DEV.1139"
+        pivoted_cholesky!(A; kwargs...) = cholesky!(A, Val(true); kwargs...)
+    else
+        pivoted_cholesky!(A; kwargs...) = cholesky!(A, RowMaximum(); kwargs...)
+    end
+
     include("linpred.jl")
     include("lm.jl")
     include("glmtools.jl")
diff --git a/src/linpred.jl b/src/linpred.jl
index 412a71c9..120f1a1b 100644
--- a/src/linpred.jl
+++ b/src/linpred.jl
@@ -104,7 +104,7 @@ end
 function DensePredChol(X::StridedMatrix, pivot::Bool)
     F = Hermitian(float(X'X))
     T = eltype(F)
-    F = pivot ? cholesky!(F, Val(true), tol = -one(T), check = false) : cholesky!(F)
+    F = pivot ? pivoted_cholesky!(F, tol = -one(T), check = false) : cholesky!(F)
     DensePredChol(AbstractMatrix{T}(X),
         zeros(T, size(X, 2)),
         zeros(T, size(X, 2)),