{"doi":"10.31234/osf.io/75vc8","title":"Assessing the Need for Non-Parametric Sample Size Calculations on Affective Sensory Judgments","abstract":"The dichotomy between certainty of results and resources is exemplified in sensory affective testing. Furthermore, the data produced through using 9-point hedonic scales has a unique underlying distribution that is dependent on consumer scale usage and the product itself. We use a combination of resampling real sensory hedonic data with simulations to characterize how the outcome of affective sensory tests change across a range of participants and product space. We found that most data is multimodal and non-parametric in nature, putting in question conventional measures of statistical power and sample size assessments that are parametric. Through a novel method of pseudo-simulation that uses the actual underlying distribution, we were able to find sample sizes and statistical power across a wide range of sample sizes. To our surprise, contrasting this new method to conventional methods of sample size estimation, gaussian sample size estimates consistently give a similar number of participants needed for a particular statistical power. Our novel method also compared similarly to sample size estimates generated from nonparametric methods. Our findings highlight the unique underlying distributions of data collected from 9-point hedonic scales and show how that distribution does not thwart conventional methods of sample size estimation.","journal":"PsyArXiv (OSF Preprints)","year":2023,"id":398886,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9393,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":774579,"name":"Martin Tchernookov","orcid":null,"position":1,"is_corresponding":false},{"id":1175058,"name":"Sara Burns","orcid":"0000-0001-6321-9075","position":2,"is_corresponding":false},{"id":1175059,"name":"Curtis R. Luckett","orcid":"0000-0003-3955-7474","position":3,"is_corresponding":false},{"id":415266,"name":"Vijay Singh","orcid":"0000-0002-7886-9190","position":4,"is_corresponding":false},{"id":231550,"name":"Robert Pellegrino","orcid":"0000-0001-7436-8826","position":0,"is_corresponding":true}],"reference_count":24,"raw_metadata":null,"created_at":"2026-07-19T01:19:51.724387Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}