StatsPAI 1.5.0 — Interference / Conformal / Mendelian family consolidation

Minor release. Three concurrent improvements to the interference,
conformal causal inference, and Mendelian Randomization families:
full-family documentation guides, unified dispatchers matching the
sp.synth / sp.decompose / sp.dml pattern, and a targeted
correctness audit that surfaced and fixed two silent-wrong-numbers
issues.

Added — three new family guides (interference / conformal / MR)

• docs/guides/interference_family.md — complete walkthrough of
  sp.spillover, sp.network_exposure, sp.peer_effects,
  sp.network_hte, sp.inward_outward_spillover,
  sp.cluster_matched_pair, sp.cluster_cross_interference,
  sp.cluster_staggered_rollout, sp.dnc_gnn_did. Decision tree
  covering partial / network / cluster-RCT designs with the 5
  diagnostics every interference analysis should report (exposure
  balance, identification check for peer_effects, overlap for
  network_hte, parallel trends for staggered-cluster, sensitivity to
  exposure function).
• docs/guides/conformal_family.md — complete walkthrough of
  sp.conformal_cate, sp.weighted_conformal_prediction,
  sp.conformal_counterfactual, sp.conformal_ite_interval,
  sp.conformal_density_ite, sp.conformal_ite_multidp,
  sp.conformal_debiased_ml, sp.conformal_fair_ite,
  sp.conformal_continuous, sp.conformal_interference. Clarifies
  the distinction between marginal and conditional coverage, with
  per-tool "when to use it" + how-to-read-disagreement guidance.
• docs/guides/mendelian_family.md — complete walkthrough of all 17
  MR functions (4 point estimators + 6 diagnostics + 3 multi-exposure
  extensions + instrument-strength F + 2 plots), organised around the
  IV1 / IV2 / IV3 assumption hierarchy. Ships the 4 sanity checks every
  MR analysis should report and a worked BMI → T2D example.

Each guide is linked from mkdocs.yml under Guides and surfaces via
sp.search_functions().

Added — unified family dispatchers

Three new top-level dispatchers mirroring the style of sp.synth /
sp.decompose / sp.dml:

• sp.mr(method=..., ...) — single entry point for the 17-function
  Mendelian Randomization family. Supports
  method ∈ {"ivw", "egger", "median", "penalized_median", "mode", "simple_mode", "all", "mvmr", "mediation", "bma", "presso", "radial", "leave_one_out", "steiger", "heterogeneity", "pleiotropy_egger", "f_statistic", ...} with aliases. kwargs pass through to the target
  function. sp.mr_available_methods() lists all aliases.

• sp.conformal(kind=..., ...) — single entry point for the
  10-function conformal causal inference family. Supports
  kind ∈ {"cate", "counterfactual", "ite", "weighted", "density", "multidp", "debiased", "fair", "continuous", "interference", ...}.
  sp.conformal_available_kinds() lists all aliases.

• sp.interference(design=..., ...) — single entry point for the
  9-function interference / spillover family. Supports
  design ∈ {"partial", "network_exposure", "peer_effects", "network_hte", "inward_outward", "cluster_matched_pair", "cluster_cross", "cluster_staggered", "dnc_gnn", ...}.
  sp.interference_available_designs() lists all aliases.

All three dispatchers are registered with hand-written schemas so
sp.describe_function("mr") / "conformal" / "interference" return
agent-readable descriptions. 30 new tests in
tests/test_dispatchers_v150.py guarantee the dispatcher path and the
direct-call path produce byte-for-byte identical results.

⚠️ Breaking — sp.mr is now a function, not a module alias

Prior to v1.5.0 sp.mr was a reference to the statspai.mendelian
submodule (from . import mendelian as mr), so sp.mr.mr_ivw(...)
worked. v1.5.0 replaces this with the new dispatcher function
sp.mr(method=..., ...).

Migration: code that previously wrote sp.mr.mr_ivw(bx, by, sx, sy)
should use the top-level sp.mr_ivw(bx, by, sx, sy) (already exported
in every prior version) or the new sp.mr("ivw", beta_exposure=bx, ...)
dispatcher. The module is still accessible as sp.mendelian for users
who were doing submodule-level introspection.

Updated references: the only in-repo consumer of the old
sp.mr.mr_ivw form was tests/reference_parity/test_mr_parity.py,
which has been migrated to top-level calls. All external user code
that already uses sp.mr_ivw / sp.mendelian_randomization / etc
continues to work unchanged.

Fixed — silent wrong numbers (correctness audit)

• sp.mr_egger — slope inference used Normal, not t(n−2). The
  companion sp.mr_pleiotropy_egger correctly used t(n−2) for the
  Egger intercept p-value, but mr_egger itself used stats.norm.cdf
  for both the slope p-value and the slope CI's critical value. This
  was anti-conservative at small n_snps: e.g. for n_snps = 5 and a
  t-stat of 1.5, the Normal-based two-sided p is 0.134 whereas the
  correct t(3)-based p is 0.231. mendelian_randomization(..., methods=["egger"])
  inherited the bug through its internal call. The fix switches both the
  p-value and the CI critical value to t(n−2). Regression guard in
  tests/test_correctness_v150.py::TestMREggerUsesTDistribution.
  For n_snps ≥ 100 the change is numerically invisible (< 1e-3 in p).

• sp.mr_presso — MC p-value could equal exactly 0. Both the
  global test p-value and the per-SNP outlier p-values used the raw
  mean(null >= obs) form, which collapses to 0.0 when the observed
  statistic exceeds every simulated null. An MC-estimated p-value
  cannot be zero — its true lower bound is 1 / (B + 1). The fix
  switches to the standard (k + 1) / (B + 1) convention (matching
  R's MR-PRESSO package). Downstream effect: reported p-values are
  now always strictly positive and in [1/(B+1), 1], which prevents
  log-transforms and sensitivity analyses from silently producing
  -inf. Regression guard in
  tests/test_correctness_v150.py::TestMRPressoMCPvalueConvention.

Fixed — dead code

• sp.network_exposure._ht_estimate contained a dimensionally
  inconsistent var = ... expression that was immediately overwritten
  by the conservative Aronow-Samii Theorem 1 bound var_as = .... The
  dead line is removed; the reported SE is unchanged.

Fixed — registry coverage

Five previously-exposed-but-unregistered family functions now surface
in sp.list_functions() and have agent-readable schemas via
sp.describe_function():

• sp.network_exposure (Aronow-Samii HT)
• sp.peer_effects (Bramoullé-Djebbari-Fortin 2SLS)
• sp.weighted_conformal_prediction (TBCR 2019 primitive)
• sp.conformal_counterfactual (Lei-Candès Theorem 1)
• sp.conformal_ite_interval (Lei-Candès Eq. 3.4 nested bound)

No other API changes

Every other public signature is byte-for-byte identical to v1.4.2.
Existing user code keeps working; upgrades reveal slightly wider Egger
CIs at small n_snps and strictly positive mr_presso p-values.