Preface |
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xi | |
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Chapter 1 Register Surveys -- An Introduction |
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1 | (24) |
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1.1 The purpose of the book |
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1 | (2) |
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1.2 The need for a new theory and new methods |
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3 | (2) |
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1.3 Four ways of using administrative registers |
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5 | (1) |
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1.4 Preconditions for register-based statistics |
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6 | (4) |
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1.4.1 Reliable administrative systems |
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7 | (1) |
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1.4.2 Legal base and public approval |
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8 | (2) |
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1.5 Basic concepts and terms |
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10 | (10) |
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1.5.1 What is a statistical survey? |
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10 | (1) |
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1.5.2 What is a register? |
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11 | (2) |
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1.5.3 What is a register survey? |
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13 | (1) |
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1.5.4 The Income and Taxation Register |
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14 | (2) |
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1.5.5 The Quarterly and Annual Pay Registers |
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16 | (4) |
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1.6 Comparing sample surveys and register surveys |
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20 | (3) |
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23 | (2) |
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Chapter 2 The Nature of Administrative Data |
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25 | (12) |
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2.1 Different kinds of administrative data |
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25 | (1) |
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2.2 How are data recorded? |
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26 | (1) |
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2.3 Administrative and statistical information systems |
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27 | (2) |
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2.4 Measurement errors in statistical and administrative data |
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29 | (1) |
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2.5 Why use administrative data for statistics? |
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30 | (2) |
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2.6 Comparing sample survey and administrative data |
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32 | (4) |
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2.6.1 A questionnaire to persons compared with register data |
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32 | (2) |
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2.6.2 An enterprise questionnaire compared with register data |
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34 | (2) |
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36 | (1) |
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Chapter 3 Protection of Privacy and Confidentiality |
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37 | (10) |
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38 | (3) |
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3.1.1 No text in output databases |
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38 | (1) |
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3.1.2 Existence of identity numbers |
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39 | (2) |
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3.2 Disclosure risks -- tables |
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41 | (4) |
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3.2.1 Rules for tables with counts, totals and mean values |
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41 | (2) |
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3.2.2 The threshold rule -- analyse complete tables |
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43 | (1) |
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3.2.3 Frequency tables are often misunderstood |
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44 | (1) |
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3.2.4 Combining tables can cause disclosure |
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45 | (1) |
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3.3 Disclosure risks -- microdata |
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45 | (1) |
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46 | (1) |
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Chapter 4 The Register System |
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47 | (30) |
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4.1 A register model based on object types and relations |
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47 | (7) |
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4.1.1 The register system and protection of privacy |
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53 | (1) |
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4.1.2 The register system and data warehousing |
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53 | (1) |
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4.2 Organising the work with the system |
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54 | (2) |
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4.3 The populations in the system |
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56 | (4) |
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4.3.1 How to produce consistent register-based statistics |
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57 | (1) |
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58 | (1) |
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4.3.3 Populations, variables and time |
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59 | (1) |
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4.4 The variables in the system |
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60 | (5) |
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4.4.1 Standardised variables in the register system |
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60 | (2) |
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62 | (1) |
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4.4.3 Variables with different origins |
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63 | (1) |
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4.4.4 Variables with different functions in the system |
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64 | (1) |
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4.5 Using the system for micro integration |
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65 | (5) |
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4.6 Three kinds of registers with different roles |
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70 | (2) |
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4.7 Register systems and register surveys within enterprises |
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72 | (2) |
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74 | (3) |
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Chapter 5 The Base Registers in the System |
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77 | (26) |
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5.1 Characteristics of a base register |
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77 | (1) |
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5.2 Requirements for base registers |
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78 | (5) |
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5.2.1 Defining and deriving statistical units |
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78 | (2) |
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5.2.2 Objects and identities -- requirements for a base register |
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80 | (1) |
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5.2.3 Coverage and spanning variables in base registers |
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81 | (2) |
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5.3 The Population Register |
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83 | (5) |
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5.4 The Business Register |
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88 | (5) |
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5.5 The Real Estate Register |
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93 | (1) |
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5.6 The Activity Register |
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94 | (4) |
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5.7 Everyone should support the base registers |
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98 | (3) |
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101 | (2) |
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Chapter 6 How to Create a Register -- Matching and Combining Sources |
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103 | (18) |
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6.1 Preconditions in different countries |
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103 | (2) |
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6.2 Matching methods and problems |
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105 | (9) |
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6.2.1 Deterministic record linkage |
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105 | (1) |
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6.2.2 Probabilistic record linkage |
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106 | (6) |
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6.2.3 Four causes of matching errors |
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112 | (2) |
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6.3 Matching sources with different object types |
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114 | (6) |
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120 | (1) |
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Chapter 7 How to Create a Register -- The Population |
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121 | (26) |
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7.1 How should register surveys be structured? |
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121 | (4) |
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7.2 Register survey design |
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125 | (6) |
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7.2.1 Determining the research objectives |
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125 | (3) |
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7.2.2 Making an inventory of different sources |
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128 | (1) |
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7.2.3 Analysing the usability of administrative sources |
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128 | (3) |
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7.3 Defining a register's object set |
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131 | (11) |
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7.3.1 Defining a population |
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131 | (3) |
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7.3.2 Can you alter data from the National Tax Agency? |
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134 | (1) |
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7.3.3 Defining a population -- primary registers |
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135 | (1) |
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7.3.4 Defining a population -- integrated registers |
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136 | (1) |
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7.3.5 Defining a calendar year population |
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137 | (1) |
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7.3.6 Defining a population -- frame or register population? |
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138 | (3) |
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7.3.7 Base registers should be used when defining populations |
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141 | (1) |
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7.4 Defining the statistical units |
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142 | (3) |
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7.4.1 Units and identities when creating primary registers |
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143 | (1) |
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7.4.2 Using administrative objects instead of statistical units |
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144 | (1) |
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7.5 Creating longitudinal registers -- the population |
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145 | (1) |
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146 | (1) |
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Chapter 8 How to Create a Register -- The Variables |
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147 | (24) |
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8.1 The variables in the register |
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147 | (4) |
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8.1.1 Variable definitions |
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148 | (1) |
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8.1.2 Variables in statistical science |
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149 | (1) |
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8.1.3 Variables in informatics |
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150 | (1) |
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8.1.4 Creating register variables -- checklist |
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151 | (1) |
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8.2 Forming derived variables using models |
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151 | (8) |
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8.2.1 Exact calculation of values using a rule |
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152 | (1) |
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8.2.2 Estimating values with a rule |
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153 | (1) |
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8.2.3 Estimating values with a causal model |
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154 | (3) |
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8.2.4 Derived variables and imputed variable values |
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157 | (1) |
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8.2.5 Creating variables by coding |
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158 | (1) |
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159 | (6) |
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8.3.1 Activity statistics |
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160 | (1) |
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8.3.2 Activity data aggregated for enterprises and organisations |
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161 | (1) |
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8.3.3 Activity data aggregated for persons: multi-valued variables |
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161 | (4) |
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8.4 Creating longitudinal registers -- the variables |
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165 | (4) |
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169 | (2) |
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Chapter 9 How to Create a Register -- Editing |
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171 | (22) |
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9.1 Editing register data |
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171 | (10) |
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9.1.1 Editing one administrative register |
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173 | (2) |
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9.1.2 Consistency editing -- is the population correct? |
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175 | (3) |
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9.1.3 Consistency editing -- are the units correct? |
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178 | (2) |
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9.1.4 Consistency editing -- are the variables correct? |
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180 | (1) |
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9.2 Case studies -- editing register data |
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181 | (4) |
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9.2.1 Editing work within the Income and Taxation Register |
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181 | (2) |
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9.2.2 Editing work with the Income Statement Register |
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183 | (1) |
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9.2.3 What more can be learned from these examples? |
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184 | (1) |
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9.3 Editing, quality assurance and survey design |
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185 | (7) |
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9.3.1 Survey design in a register-based production system |
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185 | (1) |
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9.3.2 Quality assessment in a register-based production system |
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186 | (5) |
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9.3.3 Total survey error in a register-based production system |
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191 | (1) |
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192 | (1) |
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193 | (8) |
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10.1 Primary registers -- the need for metadata |
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193 | (2) |
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10.1.1 Documentation of administrative sources |
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194 | (1) |
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10.1.2 Documentation of sources within the system |
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194 | (1) |
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10.1.3 Documentation of a new register |
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195 | (1) |
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10.2 Changes over time -- the need for metadata |
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195 | (1) |
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10.3 Integrated registers -- the need for metadata |
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196 | (1) |
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10.4 Classification and definitions database |
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197 | (1) |
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10.5 The need for metadata for registers |
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198 | (2) |
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200 | (1) |
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Chapter 11 Estimation Methods -- Introduction |
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201 | (8) |
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11.1 Estimation in sample surveys and register surveys |
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202 | (1) |
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11.2 Estimation methods for register surveys that use weights |
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203 | (1) |
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11.3 Calibration of weights in register surveys |
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204 | (3) |
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11.4 Using weights for estimation |
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207 | (1) |
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208 | (1) |
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Chapter 12 Estimation Methods -- Missing Values |
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209 | (12) |
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12.1 Make no adjustments, publish `value unknown' |
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210 | (4) |
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12.2 Adjustment for missing values using weights |
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214 | (1) |
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12.3 Adjustment for missing values by imputation |
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215 | (3) |
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12.4 Missing values in a system of registers |
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218 | (2) |
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220 | (1) |
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Chapter 13 Estimation Methods -- Coverage Problems |
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221 | (8) |
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13.1 Reducing overcoverage and undercoverage |
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221 | (3) |
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13.1.1 Coverage problems in the Population Register |
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221 | (1) |
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13.1.2 Coverage problems in the Business Register |
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222 | (2) |
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13.2 Estimation methods to correct for overcoverage |
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224 | (2) |
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13.3 Undercoverage in the administrative system |
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226 | (2) |
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228 | (1) |
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Chapter 14 Estimation Methods -- Multi-valued Variables |
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229 | (30) |
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14.1 Multi-valued variables |
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229 | (3) |
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232 | (19) |
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14.2.1 Occupation in the Activity and Occupation Registers |
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232 | (4) |
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14.2.2 Industrial classification in the Business Register |
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236 | (2) |
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14.2.3 Importing many multi-valued variables |
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238 | (4) |
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14.2.4 Consistency between estimates from different registers |
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242 | (3) |
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14.2.5 Multi-valued variables -- what is done in practice? |
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245 | (2) |
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14.2.6 Additional estimation methods |
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247 | (4) |
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14.3 Application of the method |
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251 | (3) |
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14.4 Linking of time series using combination objects |
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254 | (4) |
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14.4.1 Linking time series |
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254 | (2) |
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14.4.2 Changed industrial classification in the Business Register |
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256 | (2) |
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258 | (1) |
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Chapter 15 Theory and Quality of Register-based Statistics |
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259 | (38) |
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15.1 Is there a theory for register surveys? |
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259 | (8) |
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15.1.1 Statistical inference at a national statistical office |
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260 | (2) |
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15.1.2 Theory-based methods or ad hoc methods |
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262 | (1) |
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15.1.3 The survey approach and the systems approach |
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263 | (4) |
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15.2 Measuring quality -- why and how? |
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267 | (4) |
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15.3 Analysing administrative sources -- input data quality |
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271 | (7) |
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278 | (1) |
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15.5 The integration process -- integration errors |
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279 | (9) |
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15.5.1 Creating register populations -- coverage errors |
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280 | (2) |
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15.5.2 Creating statistical units -- errors in units |
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282 | (1) |
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15.5.3 Creating statistical variables -- errors in variables |
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283 | (5) |
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15.6 Random variation in register data |
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288 | (3) |
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15.7 The register system and data warehousing |
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291 | (4) |
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295 | (2) |
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297 | (4) |
References |
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301 | (6) |
Index |
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307 | |