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篇名
比較入選機率分組與其他加權方法對電話調查樣本的調整:上網率的推估
並列篇名
A Comparison of Propensity Score Sub-classification and other Calibration Methods based on a Telephone Sample to Estimate Internet Usage
作者 杜素豪
中文摘要
傳統的事後分層與多重反覆加權法可以降低抽樣誤差,但在改進推估偏差的效果仍然有限。本研究採用「入選機率調整法(propensity score adjustment, PSA)」,對2008年的電話訪問樣本進行18歲以上臺灣民眾之上網率的推估,進行上述兩種加權方法以及其納入PSA前後之估計效果的比較。在幾種入選機率值(propensity scores, PS)的調整方法中,本研究採用次樣本分組法,因此也同時比較四到十個分組之間估計效果的差異。本研究以同一時段蒐集的「臺灣地區社會變遷基本調查五期四次全球化組」為PSA的參考樣本;(前)行政院研究考核委員會執行的「數位落差調查」所推估的全臺灣民眾的上網率為擬母體黃金標準,亦即PSA與兩種傳統加權之估計效果的比較基準。結果證實納入原調查權數(來自事後分層與多重反覆加權)後,在五個次樣本分組時,上網率的估計值最接近數位落差調查的估計值。比起納入事後分層權數,納入多重反覆加權權數的PSA在估計誤差上相對較小。
英文摘要
While post-stratification and raking calibration methods can reduce sampling errors, they have estimation limitations. The author adopts propensity score adjustment (PSA) to estimate Internet usage based on data collected from a 2008 telephone sample. Comparisons were made among post-stratification, raking, post-stratification PSA, and raking PSA. Stratification was used to produce PS weights and to compare estimated Internet usage for seven sub-classifications. The Taiwanese Social Change Survey conducted during the same period was used as the reference sample for PSA, while official statistics based on a Digital Divide Survey as the benchmark for bias reduction comparisons. Results indicate that (a) Internet usage estimates based on PSA adjusted according to base weight (i.e., survey weight from post-stratification or raking) using five sub-classes were more accurate than other estimates, and (b) bias reduction based on PSA adjustedby raking exceeded that of PSA adjusted by post-stratification.
起訖頁 115-150
關鍵詞 事後分層多變項反覆加權入選機率調整法次樣本分組Post-StratificationRakingPropensity Score AdjustmentSub-Classification
刊名 臺灣社會學刊  
期數 201506 (56期)
出版單位 臺灣社會學會
該期刊-上一篇 照顧子女的代價:母職對臺灣女性薪資影響的貫時性分析
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