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Record W2139621222 · doi:10.1177/0165025409351386

Differences in causal estimates from longitudinal analyses of residualized versus simple gain scores: Contrasting controls for selection and regression artifacts

2010· article· en· W2139621222 on OpenAlex
Robert E. Larzelere, Emilio Ferrer, Brett R. Kuhn, Ketevan Danelia

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Behavioral Development · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyLongitudinal studyDevelopmental psychologyPunishment (psychology)ReplicateSelection (genetic algorithm)Regression analysisRegressionContrast (vision)Causal modelStatistics

Abstract

fetched live from OpenAlex

This study estimates the causal effects of six corrective actions for children's problem behaviors, comparing four types of longitudinal analyses that correct for pre-existing differences in a cohort of 1,464 4- and 5-year-olds from Canadian National Longitudinal Survey of Children and Youth (NLSCY) data. Analyses of residualized gain scores found apparently detrimental effects of all corrective actions by parents and professionals on subsequent antisocial behavior and hyperactivity. In contrast, analyses of simple gain scores found only apparently beneficial effects. Temporally reversed analyses yielded the same pattern of results, consistent with selection biases and regression artifacts, not with unidirectional causal effects. The findings were similar for corrective actions by professionals (e.g., Ritalin, psychotherapy) and by parents (physical and nonphysical punishment, scolding/yelling, “hostile-ineffective” parenting). Longitudinal analyses should check for similar artifacts by implementing temporally-reversed analyses and by determining whether causally relevant coefficients would replicate without artifacts biased in their favor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.130
GPT teacher head0.446
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it