Get quick answers to your questions about the article from our AI researcher chatbot
{'id': 'https://openalex.org/W2133478656', 'doi': 'https://doi.org/10.1002/sim.1513', 'title': 'On weighting the rates in non‐response weights', 'display_name': 'On weighting the rates in non‐response weights', 'publication_year': 2003, 'publication_date': '2003-04-14', 'ids': {'openalex': 'https://openalex.org/W2133478656', 'doi': 'https://doi.org/10.1002/sim.1513', 'mag': '2133478656', 'pmid': 'https://pubmed.ncbi.nlm.nih.gov/12704617'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1002/sim.1513', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S55189604', 'display_name': 'Statistics in Medicine', 'issn_l': '0277-6715', 'issn': ['0277-6715', '1097-0258'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320595', 'host_organization_name': 'Wiley', 'host_organization_lineage': ['https://openalex.org/P4310320595'], 'host_organization_lineage_names': ['Wiley'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-article', 'indexed_in': ['crossref', 'pubmed'], 'open_access': {'is_oa': True, 'oa_status': 'green', 'oa_url': 'http://deepblue.lib.umich.edu/bitstream/2027.42/34860/1/1513_ftp.pdf', 'any_repository_has_fulltext': True}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5072262441', 'display_name': 'Roderick J. A. Little', 'orcid': 'https://orcid.org/0000-0001-9878-6977'}, 'institutions': [{'id': 'https://openalex.org/I27837315', 'display_name': 'University of Michigan–Ann Arbor', 'ror': 'https://ror.org/00jmfr291', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I27837315']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'Roderick J. Little', 'raw_affiliation_strings': ['Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109-2029, U.S.A.'], 'affiliations': [{'raw_affiliation_string': 'Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109-2029, U.S.A.', 'institution_ids': ['https://openalex.org/I27837315']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5087633258', 'display_name': 'Sonya Vartivarian', 'orcid': None}, 'institutions': [{'id': 'https://openalex.org/I27837315', 'display_name': 'University of Michigan–Ann Arbor', 'ror': 'https://ror.org/00jmfr291', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I27837315']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'Sonya Vartivarian', 'raw_affiliation_strings': ['Department of Statistics, University of Michigan, Ann Arbor, U.S.A.'], 'affiliations': [{'raw_affiliation_string': 'Department of Statistics, University of Michigan, Ann Arbor, U.S.A.', 'institution_ids': ['https://openalex.org/I27837315']}]}], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': {'value': 4940, 'currency': 'USD', 'value_usd': 4940, 'provenance': 'doaj'}, 'apc_paid': None, 'fwci': 2.953, 'has_fulltext': True, 'fulltext_origin': 'pdf', 'cited_by_count': 151, 'citation_normalized_percentile': {'value': 0.999633, 'is_in_top_1_percent': True, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 97, 'max': 98}, 'biblio': {'volume': '22', 'issue': '9', 'first_page': '1589', 'last_page': '1599'}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T13030', 'display_name': 'Statistical Methods for Sensitive Survey Questions', 'score': 0.9981, 'subfield': {'id': 'https://openalex.org/subfields/2613', 'display_name': 'Statistics and Probability'}, 'field': {'id': 'https://openalex.org/fields/26', 'display_name': 'Mathematics'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T13030', 'display_name': 'Statistical Methods for Sensitive Survey Questions', 'score': 0.9981, 'subfield': {'id': 'https://openalex.org/subfields/2613', 'display_name': 'Statistics and Probability'}, 'field': {'id': 'https://openalex.org/fields/26', 'display_name': 'Mathematics'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T10243', 'display_name': 'Methods for Handling Missing Data in Statistical Analysis', 'score': 0.9929, 'subfield': {'id': 'https://openalex.org/subfields/2613', 'display_name': 'Statistics and Probability'}, 'field': {'id': 'https://openalex.org/fields/26', 'display_name': 'Mathematics'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T11539', 'display_name': 'Survey Methodology and Response Rates Analysis', 'score': 0.9797, 'subfield': {'id': 'https://openalex.org/subfields/3312', 'display_name': 'Sociology and Political Science'}, 'field': {'id': 'https://openalex.org/fields/33', 'display_name': 'Social Sciences'}, 'domain': {'id': 'https://openalex.org/domains/2', 'display_name': 'Social Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/survey-sampling', 'display_name': 'Survey Sampling', 'score': 0.581187}, {'id': 'https://openalex.org/keywords/nonresponse-bias', 'display_name': 'Nonresponse Bias', 'score': 0.567004}, {'id': 'https://openalex.org/keywords/estimation-methods', 'display_name': 'Estimation Methods', 'score': 0.545332}, {'id': 'https://openalex.org/keywords/response-rates', 'display_name': 'Response Rates', 'score': 0.529663}, {'id': 'https://openalex.org/keywords/survey-methodology', 'display_name': 'Survey Methodology', 'score': 0.528056}, {'id': 'https://openalex.org/keywords/inverse-probability-weighting', 'display_name': 'Inverse probability weighting', 'score': 0.49698737}], 'concepts': [{'id': 'https://openalex.org/C183115368', 'wikidata': 'https://www.wikidata.org/wiki/Q856577', 'display_name': 'Weighting', 'level': 2, 'score': 0.84225744}, {'id': 'https://openalex.org/C105795698', 'wikidata': 'https://www.wikidata.org/wiki/Q12483', 'display_name': 'Statistics', 'level': 1, 'score': 0.68787104}, {'id': 'https://openalex.org/C75373757', 'wikidata': 'https://www.wikidata.org/wiki/Q7410160', 'display_name': 'Sampling design', 'level': 3, 'score': 0.6100118}, {'id': 'https://openalex.org/C140779682', 'wikidata': 'https://www.wikidata.org/wiki/Q210868', 'display_name': 'Sampling (signal processing)', 'level': 3, 'score': 0.5034484}, {'id': 'https://openalex.org/C2779915747', 'wikidata': 'https://www.wikidata.org/wiki/Q17058619', 'display_name': 'Inverse probability weighting', 'level': 3, 'score': 0.49698737}, {'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.4812436}, {'id': 'https://openalex.org/C81917197', 'wikidata': 'https://www.wikidata.org/wiki/Q628760', 'display_name': 'Selection (genetic algorithm)', 'level': 2, 'score': 0.41323504}, {'id': 'https://openalex.org/C2908647359', 'wikidata': 'https://www.wikidata.org/wiki/Q2625603', 'display_name': 'Population', 'level': 2, 'score': 0.40535057}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.36313683}, {'id': 'https://openalex.org/C149782125', 'wikidata': 'https://www.wikidata.org/wiki/Q160039', 'display_name': 'Econometrics', 'level': 1, 'score': 0.34765196}, {'id': 'https://openalex.org/C17923572', 'wikidata': 'https://www.wikidata.org/wiki/Q7250160', 'display_name': 'Propensity score matching', 'level': 2, 'score': 0.1360268}, {'id': 'https://openalex.org/C119857082', 'wikidata': 'https://www.wikidata.org/wiki/Q2539', 'display_name': 'Machine learning', 'level': 1, 'score': 0.11184275}, {'id': 'https://openalex.org/C71924100', 'wikidata': 'https://www.wikidata.org/wiki/Q11190', 'display_name': 'Medicine', 'level': 0, 'score': 0.06994033}, {'id': 'https://openalex.org/C106131492', 'wikidata': 'https://www.wikidata.org/wiki/Q3072260', 'display_name': 'Filter (signal processing)', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C31972630', 'wikidata': 'https://www.wikidata.org/wiki/Q844240', 'display_name': 'Computer vision', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C126838900', 'wikidata': 'https://www.wikidata.org/wiki/Q77604', 'display_name': 'Radiology', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C99454951', 'wikidata': 'https://www.wikidata.org/wiki/Q932068', 'display_name': 'Environmental health', 'level': 1, 'score': 0.0}], 'mesh': [{'descriptor_ui': 'D003627', 'descriptor_name': 'Data Interpretation, Statistical', 'qualifier_ui': '', 'qualifier_name': None, 'is_major_topic': True}, {'descriptor_ui': 'D006306', 'descriptor_name': 'Health Surveys', 'qualifier_ui': '', 'qualifier_name': None, 'is_major_topic': True}, {'descriptor_ui': 'D012494', 'descriptor_name': 'Sampling Studies', 'qualifier_ui': '', 'qualifier_name': None, 'is_major_topic': True}, {'descriptor_ui': 'D015982', 'descriptor_name': 'Bias', 'qualifier_ui': '', 'qualifier_name': None, 'is_major_topic': False}, {'descriptor_ui': 'D003198', 'descriptor_name': 'Computer Simulation', 'qualifier_ui': '', 'qualifier_name': None, 'is_major_topic': False}, {'descriptor_ui': 'D006801', 'descriptor_name': 'Humans', 'qualifier_ui': '', 'qualifier_name': None, 'is_major_topic': False}], 'locations_count': 3, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1002/sim.1513', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S55189604', 'display_name': 'Statistics in Medicine', 'issn_l': '0277-6715', 'issn': ['0277-6715', '1097-0258'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320595', 'host_organization_name': 'Wiley', 'host_organization_lineage': ['https://openalex.org/P4310320595'], 'host_organization_lineage_names': ['Wiley'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, {'is_oa': True, 'landing_page_url': 'https://hdl.handle.net/2027.42/34860', 'pdf_url': 'http://deepblue.lib.umich.edu/bitstream/2027.42/34860/1/1513_ftp.pdf', 'source': {'id': 'https://openalex.org/S4306400393', 'display_name': 'Deep Blue (University of Michigan)', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I27837315', 'host_organization_name': 'University of Michigan–Ann Arbor', 'host_organization_lineage': ['https://openalex.org/I27837315'], 'host_organization_lineage_names': ['University of Michigan–Ann Arbor'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'publishedVersion', 'is_accepted': True, 'is_published': True}, {'is_oa': False, 'landing_page_url': 'https://pubmed.ncbi.nlm.nih.gov/12704617', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S4306525036', 'display_name': 'PubMed', 'issn_l': None, 'issn': None, 'is_oa': False, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I1299303238', 'host_organization_name': 'National Institutes of Health', 'host_organization_lineage': ['https://openalex.org/I1299303238'], 'host_organization_lineage_names': ['National Institutes of Health'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': {'is_oa': True, 'landing_page_url': 'https://hdl.handle.net/2027.42/34860', 'pdf_url': 'http://deepblue.lib.umich.edu/bitstream/2027.42/34860/1/1513_ftp.pdf', 'source': {'id': 'https://openalex.org/S4306400393', 'display_name': 'Deep Blue (University of Michigan)', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I27837315', 'host_organization_name': 'University of Michigan–Ann Arbor', 'host_organization_lineage': ['https://openalex.org/I27837315'], 'host_organization_lineage_names': ['University of Michigan–Ann Arbor'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'publishedVersion', 'is_accepted': True, 'is_published': True}, 'sustainable_development_goals': [], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 6, 'referenced_works': ['https://openalex.org/W2001947543', 'https://openalex.org/W2005482719', 'https://openalex.org/W2612942331', 'https://openalex.org/W3205693007', 'https://openalex.org/W4233471163', 'https://openalex.org/W4235503503'], 'related_works': ['https://openalex.org/W4238714840', 'https://openalex.org/W329462478', 'https://openalex.org/W2964635321', 'https://openalex.org/W2548795680', 'https://openalex.org/W2410123255', 'https://openalex.org/W2383809451', 'https://openalex.org/W2350399852', 'https://openalex.org/W2075598034', 'https://openalex.org/W2048805712', 'https://openalex.org/W1567644694'], 'abstract_inverted_index': {'Abstract': [0], 'A': [1], 'basic': [2], 'estimation': [3], 'strategy': [4], 'in': [5, 23, 37, 54, 68, 97, 175, 184], 'sample': [6], 'surveys': [7], 'is': [8, 89, 95, 117, 131, 187], 'to': [9, 14, 57, 84, 113, 125, 132, 146], 'weight': [10, 150], 'units': [11], 'inversely': [12], 'proportional': [13], 'the': [15, 30, 33, 43, 46, 49, 58, 61, 77, 81, 98, 108, 120, 139, 148, 152, 155, 176, 179], 'probability': [16, 158], 'of': [17, 32, 45, 48, 52, 60, 100, 104, 138, 154, 181], 'selection': [18], 'and': [19, 66, 142, 145], 'response.': [20], 'Response': [21], 'weights': [22, 51, 63, 83], 'this': [24, 160, 185], 'method': [25], 'are': [26, 111, 123], 'usually': [27], 'estimated': [28, 156], 'by': [29, 73, 80, 167], 'inverse': [31, 153], 'sample‐weighted': [34], 'response': [35, 78, 149, 157, 192], 'rate': [36], 'an': [38], 'adjustment': [39, 140, 169], 'cell,': [40], 'that': [41, 69, 75, 171], 'is,': [42], 'ratio': [44], 'sum': [47, 59], 'sampling': [50, 62, 82], 'respondents': [53, 65], 'a': [55, 136], 'cell': [56, 141], 'for': [64, 86], 'non‐respondents': [67], 'cell.': [70], 'We': [71], 'show': [72], 'simulations': [74], 'weighting': [76, 194], 'rates': [79], 'adjust': [85], 'design': [87, 109, 121, 143, 173], 'variables': [88, 110, 122, 174], 'either': [90], 'incorrect': [91], 'or': [92], 'unnecessary.': [93], 'It': [94], 'incorrect,': [96], 'sense': [99], 'yielding': [101], 'biased': [102], 'estimates': [103], 'population': [105], 'quantities,': [106], 'if': [107, 119, 178], 'related': [112], 'survey': [114, 126], 'non‐response;': [115], 'it': [116], 'unnecessary': [118], 'unrelated': [124], 'non‐response.': [127], 'The': [128], 'correct': [129], 'approach': [130, 163], 'model': [133], 'non‐response': [134], 'as': [135, 151], 'function': [137], 'variables,': [144], 'estimate': [147], 'from': [159], 'model.': [161], 'This': [162], 'can': [164, 195], 'be': [165, 196], 'implemented': [166], 'creating': [168], 'cells': [170, 182], 'include': [172], 'cross‐classification,': [177], 'number': [180], 'created': [183], 'way': [186], 'not': [188], 'too': [189], 'large.': [190], 'Otherwise,': [191], 'propensity': [193], 'applied.': [197], 'Copyright': [198], '©': [199], '2003': [200], 'John': [201], 'Wiley': [202], '&': [203], 'Sons,': [204], 'Ltd.': [205]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2133478656', 'counts_by_year': [{'year': 2024, 'cited_by_count': 4}, {'year': 2023, 'cited_by_count': 10}, {'year': 2022, 'cited_by_count': 2}, {'year': 2021, 'cited_by_count': 8}, {'year': 2020, 'cited_by_count': 8}, {'year': 2019, 'cited_by_count': 5}, {'year': 2018, 'cited_by_count': 8}, {'year': 2017, 'cited_by_count': 5}, {'year': 2016, 'cited_by_count': 9}, {'year': 2015, 'cited_by_count': 12}, {'year': 2014, 'cited_by_count': 5}, {'year': 2013, 'cited_by_count': 9}, {'year': 2012, 'cited_by_count': 11}], 'updated_date': '2024-08-22T14:44:46.537814', 'created_date': '2016-06-24'}