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Provides the quantification scheme for mapping PPDB answers to IPD values, including ranking-based rules, IPD components and variables, and links to variable coding for final IPD scores.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/ipd-indices-detailed-explanation-of-construction/204343/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/ipd-indices-detailed-explanation-of-construction/204343.png","ImageObject",300,407,{"name":42,"@type":43},"Taylor Morgan","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-18","2026-09-05",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",8,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"Which three IPD indices are constructed in this document?","Question",{"text":63,"@type":64},"The document constructs three indices: the Assembly-based IPD index (AIPD), the Plebiscitary IPD index (PIPD), and the Open plebiscitary IPD index (OIPD).","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How are PPDB item answers quantified for the main AIPD index?",{"text":68,"@type":64},"Answers are mapped to IPD values 0.00, 0.25, 0.50, 0.75, or 1.00 based on theoretical effects: unfavorable answers receive 0.00/0.25, favorable answers receive 0.75/1.00, and 0.50 is used when no specific effect can be identified.",{"name":70,"@type":61,"acceptedAnswer":71},"What is explained in the appendix regarding PPDB items?",{"text":72,"@type":64},"The appendix explains coding rules for PPDB string-variables, where text must be coded instead of using numerical values, which are used for other PPDB item types.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},204343,1788572615,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":55,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":80,"read_time":144,"preview_page_count":4},1099523885336,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","IPD-Indices – Detailed Explanation of Construction  \nIn this document the construction of the three IPD indices presented in von dem Berge and Poguntke (2017)1 is described and explained in detail. The three IPD indices are the“Assembly-based IPD index” (AIPD), the “Plebiscitary IPD index” (PIPD) and the “Open plebiscitary IPD index”(OIPD) .  \nThe document at hand consists of two parts and an Appendix:  \n(1) Part I: All items of the PPDB-Codebooks (Core Module; Modules A, B, C) which are – for theoretical reasons – relevant for IPD are listed here (including IPD-quantifications) . The selection of each item is justified and its theoretical importance on IPD is explained (theoretical derivation) .  \n(2) Part II: Explanation of the construction of the final IPD-indices with IPD-components and calculation of the final IPD-scores.  \n(3) Appendix: As some PPDB-items are string-variables, in these cases it is necessary to code text (instead of numerical values like in case of the other PPDB-items) . In the Appendix the coding rules for these string-variables are illustrated.  \nPart I: Selection of PPDB-items for the IPD-Indices  \nThe applied logic of quantification in the main AIPD index is the following: Answers to questions (PPDB-items) are attributed the values 0.00, 0. 25, 0.50, 0.75 or 1.00. The rationale behind this quantification is that all answers which – from a theoretical point of view – affect IPD unfavorably are attributed the values 0.00 or 0.25. According to the same logic all answers which affect IPD favorably are attributed the values 0.75 or 1.00. The value 0.50 is allocated to an answer when no specific effects on IPD can be identified (see example below) .  \nFurthermore, some variables are generated on the basis of ‘rankings’ of individual PPDBitems. The decisions regarding the allocation of the values to the items (questions/answers) are based on theoretical considerations, which are explained in detail in Table 1 below.  \nExample: Ideal type-example for the logic behind the allocation of IPD-values to PPDBitems (AIPD index)  \nPPDB-Question: Who has a vote on adopting the final manifesto?  \n\n| PPDB-answer-option | IPD-Value | Effect on IPD |\n| --- | --- | --- |\n| Party Congress | 1.00 (max IPD; most „inclusive“) | Pro IPD |\n| Party Sub-Units | 0.75 |  |\n| Party Legislators | 0.50 | Not explicitly pro/contra IPD |\n| Executive Commitee | 0.25 | Contra IPD |\n| Party Leader | 0.00 (min IPD; least „inclusive“) |  |\n\n1 Benjamin, Berge von dem, and Thomas Poguntke (2017): Varieties of Intra-Party Democracy: Conceptualization and Index Construction. In: Susan Scarrow, Thomas Poguntke, Paul Webb (eds. ): Organizing Political Parties. Representation, Participation, and Power. Oxford: Oxford University Press, 136-157.  \nTable 1 follows the order of the PPDB-codebook (Core Module, Module A, Module B, Module C) and consists of several columns:  \n(1) “IPD-Component”: This is mainly important for AIPD-Variables. The AIPD-Index presented in Table 2a (see Part II of this paper) consists of three different “IPDComponents” which, on their part, consist of different “IPD-Variables”. The column“IPD-Component” contains for each variable the name of the “IPD-Component” to which it belongs. For the theoretical reasons for choosing these IPD-Components see von dem Berge and Poguntke (2017) .  \n(2) “PPDB-Items(s) / IPD-Variable”: This column contains the names of the IPD-Variablesand also the code-numbers of the individual PPDB-items, which constitute the IPDVariables. AIPD-Variables are illustrated in black font color, PIPD-Variables in green fontcolor, and OPIPD-Variables in blue font color. The labels of the IPD-Variables (and the abbreviations in brackets) correspond to the variable labels in the SPSS dataset which was used to construct the indices (this SPSS dataset is available on request) .  \n(3) “Quant.” (Quantification): Here, the quantification is presented, which means the allocation of IPD-values to the individual answer-opti","cbCaigVgYpVXnJcK","https://ap.wps.com/l/cbCaigVgYpVXnJcK","pdf",306014,13,"English","# Part I: Selection of PPDB-items for the IPD-Indices\n## Quantification logic for the AIPD index\n## IPD components and IPD variables\n# Part II: Construction of the final IPD-indices\n## IPD components, IPD variables, and IPD score calculation\n# Appendix: Coding rules for string variables","[{\"question\":\"Which three IPD indices are constructed in this document?\",\"answer\":\"The document constructs three indices: the Assembly-based IPD index (AIPD), the Plebiscitary IPD index (PIPD), and the Open plebiscitary IPD index (OIPD).\"},{\"question\":\"How are PPDB item answers quantified for the main AIPD index?\",\"answer\":\"Answers are mapped to IPD values 0.00, 0.25, 0.50, 0.75, or 1.00 based on theoretical effects: unfavorable answers receive 0.00/0.25, favorable answers receive 0.75/1.00, and 0.50 is used when no specific effect can be identified.\"},{\"question\":\"What is explained in the appendix regarding PPDB items?\",\"answer\":\"The appendix explains coding rules for PPDB string-variables, where text must be coded instead of using numerical values, which are used for other PPDB item types.\"}]","IPD-Indices - Detailed Explanation of Construction | PDF",33]