diff --git a/linearmodels/__future__/ordering.py b/linearmodels/__future__/ordering.py
index e69de29bb2..58f050489f 100644
--- a/linearmodels/__future__/ordering.py
+++ b/linearmodels/__future__/ordering.py
@@ -0,0 +1,16 @@
+"""
+Opt in to formulas that do not sort variables.
+
+This was the future behavior in linearmodels 4.31. It has been the default, and
+importing this module has had no effect, since linearmodels 5.0. The module is
+kept so that existing code keeps working and will be removed in linearmodels 8.0.
+"""
+
+import warnings
+
+warnings.warn(
+    "linearmodels.__future__.ordering has no effect and will be removed in "
+    "linearmodels 8.0",
+    FutureWarning,
+    stacklevel=2,
+)
diff --git a/linearmodels/iv/absorbing.py b/linearmodels/iv/absorbing.py
index 9f001ea952..7f2e23f8c9 100644
--- a/linearmodels/iv/absorbing.py
+++ b/linearmodels/iv/absorbing.py
@@ -922,7 +922,7 @@ def _first_time_fit(
         mu_dep = (root_w.T @ dep) / denom
         mu_exog = (root_w.T @ exog) / denom
 
-        absorb_options = {} if absorb_options is None else absorb_options
+        absorb_options = {} if absorb_options is None else dict(absorb_options)
         assert isinstance(self._regressors, csc_array)
         if self._regressors.shape[1] > 0:
             if use_hdfe:
@@ -1047,11 +1047,12 @@ def fit(
             re-fitting large models when the set of absorbed variables and
             interactions are identical.
         lsmr_options : dict
-            Options to ass to scipy.sparse.linalg.lsmr.
+            Options to pass to scipy.sparse.linalg.lsmr.
 
             .. deprecated:: 4.17
 
-               Use absorb_options to pass options
+               Use absorb_options to pass options. ``lsmr_options`` will be
+               removed in linearmodels 8.0.
 
         cov_config
             Additional parameters to pass to covariance estimator. The list
@@ -1089,7 +1090,8 @@ def fit(
             if absorb_options is not None:
                 raise ValueError("absorb_options cannot be used with lsmr_options")
             warnings.warn(
-                "lsmr_options is deprecated.  Use absorb_options.",
+                "lsmr_options is deprecated and will be removed in linearmodels "
+                "8.0. Use absorb_options.",
                 FutureWarning,
                 stacklevel=2,
             )
diff --git a/linearmodels/tests/iv/test_absorbing.py b/linearmodels/tests/iv/test_absorbing.py
index ecb0203c05..2e531a8373 100644
--- a/linearmodels/tests/iv/test_absorbing.py
+++ b/linearmodels/tests/iv/test_absorbing.py
@@ -557,7 +557,8 @@ def test_against_ols(ols_data):
                 absorb = (1.0 / root_w) * wabsorb
         rank = np.linalg.matrix_rank(absorb)
         if rank < absorb.shape[1]:
-            a, b = np.linalg.eig(absorb.T @ absorb)
+            # The matrix is symmetric: eigh has real eigenvectors, eig may not
+            a, b = np.linalg.eigh(absorb.T @ absorb)
             order = np.argsort(a)[::-1]
             a, b = a[order], b[:, order]
             z = absorb @ b
@@ -756,6 +757,29 @@ def test_options(random_gen):
         mod.fit(absorb_options={"atol": 1e-7, "btol": 1e-7}, method="hdfe")
 
 
+def test_absorb_options_are_not_modified(random_gen):
+    absorb = random_gen.randint(0, 10, size=1000)
+    x = random_gen.standard_normal((1000, 3))
+    y = random_gen.standard_normal(1000)
+    dfd = {f"x{i}": pd.Series(x[:, i]) for i in range(3)}
+    dfd.update({"c": pd.Series(absorb, dtype="category"), "y": pd.Series(y)})
+    df = pd.DataFrame(dfd)
+
+    y = df.y
+    x = df.iloc[:, :3]
+    # HDFE sets drop_singletons for pyhdfe, which must not change the caller's dict
+    options = {"compute_degrees": False}
+    AbsorbingLS(y, x, absorb=df[["c"]]).fit(absorb_options=options)
+    assert options == {"compute_degrees": False}
+
+    # Otherwise these options could not be used by LSMR, which rejects drop_singletons
+    options = {}
+    AbsorbingLS(y, x, absorb=df[["c"]]).fit(absorb_options=options)
+    mod = AbsorbingLS(y, x, absorb=df[["c"]])
+    mod.fit(absorb_options=options, method="lsmr", use_cache=False)
+    assert options == {}
+
+
 def test_lsmr_annihilate_empty():
     gen = np.random.default_rng(0)
     x = csc_array(gen.standard_normal((1000, 2)))
diff --git a/linearmodels/tests/iv/test_c_stat.py b/linearmodels/tests/iv/test_c_stat.py
index cc47bf3556..478aec7264 100644
--- a/linearmodels/tests/iv/test_c_stat.py
+++ b/linearmodels/tests/iv/test_c_stat.py
@@ -75,8 +75,8 @@ def test_c_stat_against_r(row):
     res = build_model(row).fit(cov_type="robust")
     c_stat = res.c_stat(row.tested.split() or None)
     assert_allclose(c_stat.stat, row.c_stat, rtol=1e-6)
-    # pval is 1 - cdf, so it cannot resolve tail probabilities below about 1e-16
-    assert_allclose(c_stat.pval, row.pvalue, rtol=1e-5, atol=1e-12)
+    # pval is the survival function, so it is accurate far into the tail: no atol
+    assert_allclose(c_stat.pval, row.pvalue, rtol=1e-8)
     assert c_stat.df == row.df
     # The Hansen J statistic of the original model uses the same GMM steps
     assert_allclose(res.j_stat.stat, row.hansen_j, rtol=1e-6, atol=1e-8)
diff --git a/linearmodels/tests/test_deprecations.py b/linearmodels/tests/test_deprecations.py
new file mode 100644
index 0000000000..7155d0618b
--- /dev/null
+++ b/linearmodels/tests/test_deprecations.py
@@ -0,0 +1,129 @@
+"""
+Tests of the features that are deprecated and will be removed in linearmodels 8.0
+
+Remove the tests of a feature when the feature is removed.
+"""
+
+import importlib
+from pathlib import Path
+import re
+import subprocess
+import sys
+
+import numpy as np
+from numpy.testing import assert_allclose
+import pandas as pd
+import pytest
+
+from linearmodels.iv.absorbing import AbsorbingLS
+
+LSMR_OPTIONS_MESSAGE = (
+    "lsmr_options is deprecated and will be removed in linearmodels 8.0"
+)
+ORDERING = "linearmodels.__future__.ordering"
+ORDERING_MESSAGE = (
+    "linearmodels.__future__.ordering has no effect and will be removed in "
+    "linearmodels 8.0"
+)
+
+
+@pytest.fixture
+def absorbing_data():
+    # Two crossed factors, so that LSMR needs more than one iteration
+    rng = np.random.default_rng(20261011)
+    nobs = 300
+    cat = pd.DataFrame(
+        {
+            "a": pd.Series(rng.integers(0, 12, nobs), dtype="category"),
+            "b": pd.Series(rng.integers(0, 9, nobs), dtype="category"),
+        }
+    )
+    x = pd.DataFrame(rng.standard_normal((nobs, 2)), columns=["x0", "x1"])
+    effects = cat["a"].cat.codes.to_numpy() + 0.5 * cat["b"].cat.codes.to_numpy()
+    y = pd.Series(x.sum(axis=1).to_numpy() + effects + rng.standard_normal(nobs))
+    return y, x, cat
+
+
+def test_lsmr_options_warns_of_removal(absorbing_data):
+    y, x, cat = absorbing_data
+    mod = AbsorbingLS(y, x, absorb=cat)
+    with pytest.warns(FutureWarning, match=re.escape(LSMR_OPTIONS_MESSAGE)) as record:
+        mod.fit(method="lsmr", lsmr_options={})
+    matches = [w for w in record if LSMR_OPTIONS_MESSAGE in str(w.message)]
+    assert len(matches) == 1
+    # The warning points at the call to fit
+    assert Path(matches[0].filename).resolve() == Path(__file__).resolve()
+
+
+def test_lsmr_options_docstring_says_when_it_is_removed():
+    doc = AbsorbingLS.fit.__doc__
+    if doc is None:
+        pytest.skip("Docstrings are not available")
+    # The text of the parameter, with whitespace normalized to ignore line breaks
+    text = doc.partition("lsmr_options :")[2].partition("cov_config")[0]
+    block = " ".join(text.split())
+    assert ".. deprecated:: 4.17" in block
+    assert "will be removed in linearmodels 8.0" in block
+
+
+def test_lsmr_options_are_still_used(absorbing_data):
+    y, x, cat = absorbing_data
+    # One iteration is far from the solution that the default options find
+    options = {"maxiter": 1}
+    default = AbsorbingLS(y, x, absorb=cat).fit(method="lsmr", use_cache=False)
+    expected = AbsorbingLS(y, x, absorb=cat).fit(
+        method="lsmr", absorb_options=options, use_cache=False
+    )
+    assert np.max(np.abs(default.params - expected.params)) > 1e-3
+
+    with pytest.warns(FutureWarning, match="lsmr_options"):
+        res = AbsorbingLS(y, x, absorb=cat).fit(
+            method="lsmr", lsmr_options=options, use_cache=False
+        )
+    assert_allclose(res.params, expected.params, rtol=1e-10)
+    assert_allclose(res.std_errors, expected.std_errors, rtol=1e-10)
+
+
+@pytest.fixture
+def forget_ordering():
+    """Make the next import of the ordering module run the module again"""
+    package = importlib.import_module("linearmodels.__future__")
+    module = sys.modules.pop(ORDERING, None)
+    attribute = package.__dict__.pop("ordering", None)
+    yield
+    sys.modules.pop(ORDERING, None)
+    package.__dict__.pop("ordering", None)
+    if module is not None:
+        sys.modules[ORDERING] = module
+    if attribute is not None:
+        package.ordering = attribute
+
+
+@pytest.mark.parametrize(
+    "statement",
+    [
+        "import linearmodels.__future__.ordering",
+        "import linearmodels.__future__.ordering as ordering",
+        "from linearmodels.__future__ import ordering",
+    ],
+)
+def test_ordering_warns_of_removal(forget_ordering, statement):
+    # The module only runs on its first import, so run the statement as if it was
+    # in another file, on line 2, to check where the warning points
+    code = compile(f"\n{statement}\n", "importing_module.py", "exec")
+    with pytest.warns(FutureWarning, match=re.escape(ORDERING_MESSAGE)) as record:
+        exec(code, {})  # noqa: S102
+    matches = [w for w in record if ORDERING_MESSAGE in str(w.message)]
+    assert len(matches) == 1
+    assert matches[0].filename == "importing_module.py"
+    assert matches[0].lineno == 2
+
+
+def test_ordering_warns_in_a_new_interpreter():
+    # The module only runs on its first import in a process, so use a new interpreter
+    # to check what a user sees. -W makes this independent of PYTHONWARNINGS
+    code = "\nfrom linearmodels.__future__ import ordering\n"
+    cmd = [sys.executable, "-W", "default::FutureWarning", "-c", code]
+    proc = subprocess.run(cmd, capture_output=True, text=True, timeout=300, check=False)
+    assert proc.returncode == 0, proc.stderr
+    assert f"<string>:2: FutureWarning: {ORDERING_MESSAGE}" in proc.stderr
diff --git a/linearmodels/tests/test_examples.py b/linearmodels/tests/test_examples.py
index ca2f3ad3c1..23b63eb929 100644
--- a/linearmodels/tests/test_examples.py
+++ b/linearmodels/tests/test_examples.py
@@ -21,7 +21,10 @@
     kernels = jupyter_client.kernelspec.find_kernel_specs()
 
     plat_win = sys.platform.startswith("win")
-    if plat_win and (3, 8) <= sys.version_info < (3, 15):  # pragma: no cover
+    # The default Proactor event loop on Windows lacks the add_reader that zmq needs,
+    # and zmq warns that it falls back to a selector thread. The policy functions
+    # that avoid this are deprecated in Python 3.14, so only use them before that.
+    if plat_win and sys.version_info < (3, 14):  # pragma: no cover
         import asyncio
 
         try:
@@ -55,6 +58,10 @@ def notebook(request):
     return request.param
 
 
+# Windows, Python 3.14+: ignore the zmq warning about the Proactor loop (see above)
+@pytest.mark.filterwarnings(
+    "ignore:Proactor event loop does not implement add_reader:RuntimeWarning"
+)
 @pytest.mark.slow
 @pytest.mark.example
 @pytest.mark.skipif(SKIP, reason="Required packages not available")