Pith Number

pith:GY5PNVZM

pith:2026:GY5PNVZM3MANDL6TC2D72KPDWF

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Multiple-group (Controlled) Interrupted Time Series Analysis with Higher-Order Autoregressive Errors: A Simulation Study Comparing Newey-West and Prais-Winsten Methods

Ariel Linden

Prais-Winsten regression provides valid inference under higher-order autoregressive errors in multiple-group interrupted time series analysis while OLS with Newey-West errors does not.

arxiv:2603.24814 v3 · 2026-03-25 · stat.AP

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\pithnumber{GY5PNVZM3MANDL6TC2D72KPDWF}

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Claims

C1strongest claim

The tradeoff between power and valid inference seen under AR1 errors worsens with higher order autocorrelation. Under highly persistent autocorrelation, OLS-NW coverage fell to 45 to 50 percent at 100 time points, while PW maintained 91 to 94 percent coverage. PW provides more reliable inference and is preferred for hypothesis testing and error control.

C2weakest assumption

The specific AR2 and AR3 parameterizations used in the simulations (mild, oscillatory, highly persistent) are representative of autocorrelation structures encountered in actual multiple-group healthcare time series data.

C3one line summary

Prais-Winsten regression maintains valid inference under AR2 and AR3 errors in MG-ITSA simulations, while Newey-West shows inflated type I error rates up to 57% and coverage as low as 45%.

Receipt and verification

First computed	2026-05-26T01:03:28.792137Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

363af6d72cdb00d1afd31687fd29e3b1461603c519642b01807938df71a98d9b

Aliases

arxiv: 2603.24814 · arxiv_version: 2603.24814v3 · doi: 10.48550/arxiv.2603.24814 · pith_short_12: GY5PNVZM3MAN · pith_short_16: GY5PNVZM3MANDL6T · pith_short_8: GY5PNVZM

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GY5PNVZM3MANDL6TC2D72KPDWF \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 363af6d72cdb00d1afd31687fd29e3b1461603c519642b01807938df71a98d9b

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "a24b5f8058b2f187c6a4f34df58302701b1c423b246ebb3b60eea0ee2828e72e",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.AP",
    "submitted_at": "2026-03-25T20:52:35Z",
    "title_canon_sha256": "132cf6379996a4dbb25a6e39a7f6935ed85b7a5e15a1ccb829724b27da20238c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2603.24814",
    "kind": "arxiv",
    "version": 3
  }
}