{"product_id":"handbook-of-statistical-data-editing-and-imputation-563-wiley-handbooks-in-survey-methodology-9780470542804","title":"Handbook of Statistical Data Editing and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eA practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques           Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction to Statistical Data Editing and Imputation 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Statistical Data Editing and Imputation in the Statistical Process 4\u003c\/p\u003e \u003cp\u003e1.3 Data, Errors, Missing Data, and Edits 6\u003c\/p\u003e \u003cp\u003e1.4 Basic Methods for Statistical Data Editing and Imputation 13\u003c\/p\u003e \u003cp\u003e1.5 An Edit and Imputation Strategy 17\u003c\/p\u003e \u003cp\u003eReferences 21\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Methods for Deductive Correction 23\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 23\u003c\/p\u003e \u003cp\u003e2.2 Theory and Applications 24\u003c\/p\u003e \u003cp\u003e2.3 Examples 27\u003c\/p\u003e \u003cp\u003e2.4 Summary 55\u003c\/p\u003e \u003cp\u003eReferences 55\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Automatic Editing of Continuous Data 57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 57\u003c\/p\u003e \u003cp\u003e3.2 Automatic Error Localization of Random Errors 59\u003c\/p\u003e \u003cp\u003e3.3 Aspects of the Fellegi–Holt Paradigm 63\u003c\/p\u003e \u003cp\u003e3.4 Algorithms Based on the Fellegi–Holt Paradigm 65\u003c\/p\u003e \u003cp\u003e3.5 Summary 101\u003c\/p\u003e \u003cp\u003e3.A Appendix: Chernikova’s Algorithm 103\u003c\/p\u003e \u003cp\u003eReferences 104\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Automatic Editing: Extensions to Categorical Data 111\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 111\u003c\/p\u003e \u003cp\u003e4.2 The Error Localization Problem for Mixed Data 112\u003c\/p\u003e \u003cp\u003e4.3 The Fellegi–Holt Approach 115\u003c\/p\u003e \u003cp\u003e4.4 A Branch-and-Bound Algorithm for Automatic Editing of Mixed Data 129\u003c\/p\u003e \u003cp\u003e4.5 The Nearest-Neighbor Imputation Methodology 140\u003c\/p\u003e \u003cp\u003eReferences 158\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Automatic Editing: Extensions to Integer Data 161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 161\u003c\/p\u003e \u003cp\u003e5.2 An Illustration of the Error Localization Problem for Integer Data 162\u003c\/p\u003e \u003cp\u003e5.3 Fourier–Motzkin Elimination in Integer Data 163\u003c\/p\u003e \u003cp\u003e5.4 Error Localization in Categorical, Continuous, and Integer Data 172\u003c\/p\u003e \u003cp\u003e5.5 A Heuristic Procedure 182\u003c\/p\u003e \u003cp\u003e5.6 Computational Results 183\u003c\/p\u003e \u003cp\u003e5.7 Discussion 187\u003c\/p\u003e \u003cp\u003eReferences 189\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Selective Editing 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 191\u003c\/p\u003e \u003cp\u003e6.2 Historical Notes 193\u003c\/p\u003e \u003cp\u003e6.3 Micro-selection: The Score Function Approach 195\u003c\/p\u003e \u003cp\u003e6.4 Selection at the Macro-level 208\u003c\/p\u003e \u003cp\u003e6.5 Interactive Editing 212\u003c\/p\u003e \u003cp\u003e6.6 Summary and Conclusions 217\u003c\/p\u003e \u003cp\u003eReferences 219\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Imputation 223\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 223\u003c\/p\u003e \u003cp\u003e7.2 General Issues in Applying Imputation Methods 226\u003c\/p\u003e \u003cp\u003e7.3 Regression Imputation 230\u003c\/p\u003e \u003cp\u003e7.4 Ratio Imputation 244\u003c\/p\u003e \u003cp\u003e7.5 (Group) Mean Imputation 246\u003c\/p\u003e \u003cp\u003e7.6 Hot Deck Donor Imputation 249\u003c\/p\u003e \u003cp\u003e7.7 A General Imputation Model 255\u003c\/p\u003e \u003cp\u003e7.8 Imputation of Longitudinal Data 261\u003c\/p\u003e \u003cp\u003e7.9 Approaches to Variance Estimation with Imputed Data 264\u003c\/p\u003e \u003cp\u003e7.10 Fractional Imputation 271\u003c\/p\u003e \u003cp\u003eReferences 272\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Multivariate Imputation 277\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 277\u003c\/p\u003e \u003cp\u003e8.2 Multivariate Imputation Models 280\u003c\/p\u003e \u003cp\u003e8.3 Maximum Likelihood Estimation in the Presence of Missing Data 285\u003c\/p\u003e \u003cp\u003e8.4 Example: The Public Libraries 295\u003c\/p\u003e \u003cp\u003eReferences 297\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Imputation Under Edit Constraints 299\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 299\u003c\/p\u003e \u003cp\u003e9.2 Deductive Imputation 301\u003c\/p\u003e \u003cp\u003e9.3 The Ratio Hot Deck Method 311\u003c\/p\u003e \u003cp\u003e9.4 Imputing from a Dirichlet Distribution 313\u003c\/p\u003e \u003cp\u003e9.5 Imputing from a Singular Normal Distribution 318\u003c\/p\u003e \u003cp\u003e9.6 An Imputation Approach Based on Fourier–Motzkin Elimination 334\u003c\/p\u003e \u003cp\u003e9.7 A Sequential Regression Approach 338\u003c\/p\u003e \u003cp\u003e9.8 Calibrated Imputation of Numerical Data Under Linear Edit Restrictions 343\u003c\/p\u003e \u003cp\u003e9.9 Calibrated Hot Deck Imputation Subject to Edit Restrictions 349\u003c\/p\u003e \u003cp\u003eReferences 358\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Adjustment of Imputed Data 361\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 361\u003c\/p\u003e \u003cp\u003e10.2 Adjustment of Numerical Variables 362\u003c\/p\u003e \u003cp\u003e10.3 Adjustment of Mixed Continuous and Categorical Data 377\u003c\/p\u003e \u003cp\u003eReferences 389\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Practical Applications 391\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 391\u003c\/p\u003e \u003cp\u003e11.2 Automatic Editing of Environmental Costs 391\u003c\/p\u003e \u003cp\u003e11.3 The EUREDIT Project: An Evaluation Study 400\u003c\/p\u003e \u003cp\u003e11.4 Selective Editing in the Dutch Agricultural Census 420\u003c\/p\u003e \u003cp\u003eReferences 426\u003c\/p\u003e \u003cp\u003eIndex 429\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48864632734039,"sku":"9780470542804","price":142.16,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470542804.jpg?v=1722272817","url":"https:\/\/bookcurl.com\/products\/handbook-of-statistical-data-editing-and-imputation-563-wiley-handbooks-in-survey-methodology-9780470542804","provider":"Book Curl","version":"1.0","type":"link"}