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- Caitlin Henry
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1 96/10/03 : 96/03/16 : Journal of Educational Measurement & Evaluation Studies Vol. 8, No. 23, Autumn '() 23!" #$ : 1! )'( #$%&.*+%) #,- ) %& /$0 9$ 786' 5 " 2) 4!1 2$) 3$) >"? < =9$$ ": 5 $$!8 ; : " E(: " ) 5 5 B $ 5C( " $ 9B$ ( " 3$) 21 C$F "-B 3$) L 3 "K GJ: 8 I( H" I(.5= G F 5@ $ 5: NO; ";$ 9M: " ) "-B I( 5 : 2$) ; "5 F! " (.; $T Q 55 RC S( 5@ $ 5:P 5 V <! 9$ )!1 DQ.5 5 ; 5: NO; 3$) B " 3$) D8 5.T W$) 5 W$) F5; 5 (() Y(Z C$F "-B 5:P (" "]1 HM I\) " E(: " ) (( Y(Z : 5:P 3$) I_". ^Q5 $ 5 : I( D.c " I(.5 C ; b( a(r F` "..; 9(c 3$) DV! E W$) 5 H=c $T K 786' $ ( B " E(: (() :$%2 /1.3$) dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd d"$ 2C$ 5 3$) ('\(4 fg 5V( ($» FR ;5 $ 8 I(. 1.9$ «BF (T`T` OR \!5 2C$ ;5 C!5 :#jdddk dddk() (dddt`t` dddor \ddd!5 dddddd 2Cddd$ ddd ddd!5 (falsafinejad@yahoo.com (T`T` OR \!5 2C$!5
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3 F: 2$) 3$) 5 5Q 2$) #5 "?\ ( " "? BF.9k (=)FV 9$ 5 W$) "2$) B ; 5 = ; wq W$) "2$) 5 5 H=c F\!"v) B I(.( FV" I(5)! D; T$M 21 : ( $ m R 5$ V" 2$) 3$) 5 5 H=c "2$) " ; Q 5 k; g: 5 I( H=c q) 5; T$M 5 I( D; F: c 55 W$) $ ; D; 55 RC "? C$F "-B n "21 g4 g f 2"; H=c V" I( C (C" " ) C$F "-B 5 5 :4 5: 5: NO; :"5 K DV $ : 3$) ; ` D >: p FV" I$ p $ FV$") 5:P Y$ I( ; (MCAR) 5 5: NO; 3$).( F: I( 5.55 " (C" " ) C$F "-B 5 2$) F 8 `T: x" 5 $ 2$) S( F W$) 9 Z ( ( 5 9@. ; ` ) $ \(5 "2$) F W$) # c 6 5: 3$) ; c 5.5 V; "y y 8 V 5 \ k W$) 5 2$) F 8 2$) I(:DV!.9$ V; "y ( $ \(5 "2$) \ k 3$) 5 2$) W$) 8 ; 9$ 5:P n 3$).5= G 2$) F I = W$) W$) I( 8 y: ; M 55 dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. Dillman et al 2. Bhaskaran & Smeeth 3. Seaman et al 4. Tang, Little & Raghunathan 5. missing completely at random (MCAR) 6. missing at random (MAR)
4 6: $6 $;/ %4) 10 C 5 B 2(' g: 5: ( 5: NO; "3$) \3$) 5 9z5 5:P 3$) ; c 5.5$ ( $ 55 2$) 3$) 5 5 " (q() B 2(' " (2"; f D.c "5 F ET: V" ; 9(5 F: I(. " 2 5; ( 1 52 c 5 ;?3 F5 H 2$) 3$) 5 5 H=c "<T $ < I(:. 4 H u3 ; (C" (() ( Y(Z 5 9$ 786' 5 T. "F ( F` ". m ("$ 9$?(=) DQ m. DQc ; :OV! P 3$) 21 "5 F! (2004) 5 H) ( (2002) 4 (1994) 3 { "5 l4: F\!"v) B 5 (5 "2"v) k 5 x" c p; H=c F GJ: 4: F 3$) 5 5 W$) 5 F H=c 3$) K "2"v) 5 : 5.5 ) I( F: "F 5 45 ^(` g: H=c V" I 2) 5 3$) OV! I (5 G «C:» $ F\!"v) B : 9$ }R 2$) 3$) 5 #~.; wq L 3 " ) "-B 5 3$) I\ ) 5 5 3$) (2009) 6 F(((5 q:k: ; "8 3$) (2003) (2000) 7 Fk F $: 5S "8 5 E(: 5 3$) (2012) 8 I; w" 8 5 -B 5 5 " ) 5 "$ I( YP.9$ $ B$ z5 # dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. overestimate 2. underestimate 3. Roth 4. Azar 5. Peugh & Enders 6. Cao, Tsiatis and Davidian 7. Mcdonald, Thurston & Nelson 8. Graham & Coffman
5 11... : 5 B 9$5 I( ("<T $ "# Y(Z _) (C" " ) ( ~ $ ) C$F "-B ;. 5 4: " E(: "]1 m F5; 5 Y(Z -B $ : "\ 8 I( 5 "]1 HM I\ (C" ) b) ; 5 ( Y(Z 9M: "8 k HOB $ I(. $ " E(: 3$) 5: NO; 3$) 9 Z 5 3$) L 3 "K 5:P 3$) GJ: 5 m ( 5. 5:P W$) ( 2$) 5 7$ I(. 5: NO; 3$) :4 Y: : 55 3$) K " (C" " ) C$F "-B " ( d1 ; $) B ( 5 9Q5 2"; $ 15 H=c 3$) (5 "-B B F ($ 7$ <T $ 3$) ($ F) 5: 3$) n 5 =G F' d2 C$F "-B 5 B $ ($ 5) 5:P 9$ \1 (C" " ^(` 3$) L 3 "K 9M: 5:P 5: 3$) GJ: 1 '" ; 8 ( ^ ) $ " u3 $T 'w 5@ $ 2 R 5 2( ƒ` S( \ YQ 5 (1994) 9$ 5 "55 RC :? I( 7$.5 $ SAS/IML I( 5. 5 (3$) n 3$) K) 9M: "9 Z ; 3$) n 5 5: 3$)» «3$) L 3 "K» GJ: 8 dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. Kromrey & Hines 2. two-factor experimental design
6 6: $6 $;/ %4) 12 I(.5 Q ( 5 C$ F "-B «5:P /5 5 2/5 3$) "K ; 5C( «Q» 55 RC S( 5 5:P 5: "9 Z RC S( 5@ $. "B C 3$) L 3 9 Z 18 $ S( D.c b( F: 2"v) I( 5 Q S( < () 55 k(8 3$) G 5 (2"; S( (3$) F) D;.5;. Q 5 «5:» H=c "K I( 5: 9c 5 "-B H=c 5: `.5 2/5 #~.5.5 2/5 H=c DR.5 T$M Q 5 C$F S( " E(: : 5 #R 55 RC I( 4 '"10 S( 5:P 9c 5.5 V 3$) 9M: C$F "-B F 5 \(5 5 D; " I(:z ; 5 I 5 H=c DR I(.5. 5: ` 5 D; " I(:I() ; 5 : 5 5C( (I() ( z " F5).B 5 F 5 3$) K $ 5 3$) 5 F(\3$) 5C(."5 "$ 2C$ 5 3$) "9 Q w: D : 57B S( I( p"2$) F "5 4 ( R 9$ BF 2 4( ( "9 Q I( V( g: DR 5 ; (5 ;$ 1 4 FR $T I( 54.5 "B 7 $5 5 2"v) I( F 8 ""9 Z 4( I( : 5; "B S; "55 :?.9( 9$5 3$) n "\ "T F 5 5C( 5!$) 4 5. g $T R ; '/ «(» ; 9$ 9$5 2$) 30 D dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. super population 2. subpopulation
7 13... : ") 9$ 1 c $ B!; "F $ '; 4 : 1 ; 9$ «5(» «$» «;» «NO.» T:: W$) L` 5 2$) ; ' \(5 2$) 10 2$) 30 I( ; 5.( "5» 5 m. «; 9 Z 9(Z» \ kt" I(. 9T~ Q «; 9 Z 9(Z» «(.5 m 5 ]O k ( Y(Z FR Y(Z Y(Z :TR 8 I( 5 $ 5 "-B «(» \ kt") ( Y(Z F5; 5? (() E(: "]1 5 D; " E(: I\ («; 9(Z» \!" "-B I( 8.D; " E(: HM D; " (@ 13867) D; 55 RC 7$ «(» $.9$ (1) #4 ƒ K «/': 5 $» $;/6 5%$ /, G'6H (1) DB L2 / - P0 P0 P0 '# *8: O$($ $7 Q Q D ' 25,$ MN2 9/ /4 0/596 0/811 0/788 5 YQ 5 (1) #4 5 $ 5 "-B ' 3$) GJ: Dc m I(.5 $ ( HM) B $ v( : 4 ( $ 2/5 3$) K #~ p 5 m 5 3$) K 5C( d (.5 "-B C( 5 pq 7$ 5 -B T$M d2. T$M (2"; 55 RC (1) #4 \!" dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. three-stage cluster sampling
8 6: $6 $;/ %4) 14 S:S: E(: $5 T: '"10 5 : 2 1 Dc V: d3 5 B $ T(8: F5 9$5 5 "-B."-B 5S)' 5:P 5: 3$) GJ: 9k3. 23 g1 5 " (.5 $ "-B 5 B 2(' F GJ: qr$ $ $ T;: FR "-B 5 B E I\ F q). F a(r 3$) GJ: F() 5.5 Q 4: 5 B. "B $ "? I(:5;) V( FR I\ F` $; $TH 10 7/5 5 2/5 3$) "K -B 9!" $ (1) DV 5 5:P 3$) 5: NO; 3$) 9M: I() " 5 F 5 5:P 3$) z " 5 F 5 $ Y4 5: NO; 3$) (5 m ; `F"."5 F! HM ( 5 ; F$) 5 "-B "-B D8 5.(9$ )!1 DQ ; 5 "! " 3$) 9M: HM ( Y(Z F5; 5 (() Y(Z KT; 3$) K 2(' ; M 5; 15 5:P.5 5' $ " 5:P 3$) 9M: "]1 " I\ "-B 15 () " 3$) 9M: $ 15 (z (z " $) ( p (52) 9T~ $ D( 5B 9$ "]1 ( I\ ; ' "55 : 5 }R I( qvr.( 2"; "]1 I\ H=c "55 $ 5 "-B () " $) nq nz ( ; 9 T: RQ I1 " HM.9$ 55 K $
9 15... : ;) #c " 5 5 $; " n: () ( (z " H=c.( 2"; g.5 5 3$) K q) "-B 5 4 "$ $ 5 5; 0/1 ~;c.5 5 3$) K : ; ` "5 K 5; 5 (5 ( Y(Z F5; 5 (() Y(Z KT;.$ ' 0/ z v(! 3$) "K 30 5:P 3$) 9M: D; "55 < I( F5; 5 (() Y(Z ( 5 5 0/588 (z " ; DV! ' ( Y(Z.5 5 0/5 ; 0/811 0/3 3$) K F" 9M: 0/596 ( Y(Z ; ` 9$.5 5
10 6: $6 $;/ %4) 16 MN2 *8: 25,$ ' '# O$($ D P0 Q P0 Q P0 $7 - X-H W%S M 6 5 : $; (1) L )4H$Y )4H Z2
11 17... : 16 : I\ ; M k" 3$) GJ: 9M: I\ ; "]1 : ~;c "]1 9$ 5; ( 52 $ 15 c (z " $) 5 ; w$ ]1 '4 ) c 6/5 3$) 5 " I\ 9$ IV #~.(9$ 5; c 3$)! GJ: D /4 ( 70/4 58/ T$M \ k " " «8» I\ T$M \ k I\ 8 k ` W$) 5 H=c I(.55 " «5 :» "]1 "]1 GJ: I1 ; c 5 5 " I\ 8 y: }R.5 " 9Tk! $ }R (z " 5:P 3$) " E(: : I(.9$ \!" "-B " 5 () D; "55 " E(: (2) DV p T: D; "55 5 (z k " 5 5 : ( 9$ 9$ 1 (: ; "5 F! " E(: "]1 ( q( I\ : ; 5 54 z 9Tk! q( (z " \(5 TR.; D( 5B 9$ 9Tk :( GJ: ' g F 5 3$) F55 K 5 () ".95 "B " () " 5 3$)
12 6: $6 $;/ %4) 18 L2 / /': 5 $, G'6H (2) L : 9 $; $TH g B F$ T : "-B 5 HM (3) DV 3$) 9M: /5 5 2/5 3$) "K 3$) K 2(' ; 9$ V NO;."5 F! 5:P 5: ( 2(' ' \!" "-B 5 B (5:P ( 5:) :TG 3$) z "K 5 C$F "-B "5 (. :F` DQP 3$) "5 B " ( (() < "-B 5 " (z " 5) 5:P 3$) n 5! 5: HM I\) (C" "-B 5 ; c 5 9$ (() 5 5: 3$) "5 B (" E(: "]1 9c I( 5.5 :V $) K q) F 5:P n 3$) n 5! 5: 3$) 5 "-B 5 B '.9$ 5:P
13 19... : MN2 *8: 25,$ ' '# O$($ D P0 Q P0 Q P0 $7 - X-H W%S M 6 5 : 9 (3) L )4H$Y )4H \Z2
14 6: $6 $;/ %4) 20 3$) 5 "-B 5 B ; "5 F! (3) DV " I(.9$ 5:P 3$) 5 "-B 5 B! 5: «5:» H=c 5: NO; 3$) 5 ; 9 Q I( : 5 " 5: `) "55 n: : 5 }R 5 3$) 5 ( H=c 5 : $ " I() " z "! g$ ; I() ( z " 5 F g: H=c 5 5:P q( 2"; I( 5. 5 " 5 ;) 5C( 5 5 " q( \(5 TR. k" 5: 3$) 9Tk 3$) (2"; f! 5: 3$) (2"; f 3$) 5 "-B 5 $ I ; :@:.9$ 5:P "-B 5 B () " (z " 5:P ' I(.9$ () " 3$) ; ' (z " 3$) 5 (z " n: p55 (1) DV 5 D; 55 RC " E(:! z " 5 H=c I( 9$ () " n:!.i() " 5 H=c : 5 C (q( 2";) "55 k" 9 G O$($ $TH "5 $ ( HM) B 4 3$) GJ: F;: 5 F" ` ' 9 ; 5 I( Y;:.9$ $ C$F "-B #4.9$ $ DQ (q( $ E nc) 1 B E I\ YQ 2/5 3$) "K \!" "-B B E I\ D (2) 5:P n 5 5: 3$) 9M: /5 5.9$.9$ >"" (3) (1) "DV " ( 2 ; (2) #4 b( "-B " "5 B E I\ 3$) K 2(' " V DV 5:P 3$) 5 2(' I( ; M ( 2(' dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. mean square error
15 21... : I\ 8 z 3$) "K 5 I_".9$ 5: 3$)! 3$) ) $ B "5F! ; 5 w B E.9$ \!" "-B "5 5 g4: DQ (5:P 5 B E I\ (.5 5 2/5) 3$) I() "K 5 '4! 5:P " 5: 3$) " F5; 5 (() Y(Z (B E I\ 5 ' " E(: I\ OR.9$ (1) "DV $ 5 V(.9$" E(: "]1! Y: " 5 )!1 DQ "ˆ ; (.5 5 5:P 3$) K (3) I\ ;mm. 5 " I\ ' B E I\ 5 5:P 3$) K 9M: I(. k" "]1 B B E.5; ( < c '.5
16 6: $6 $;/ %4) 22 5(S] : (MSE) 9 G O$($ < (2) DB
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18 6: $6 $;/ %4) 24 W%S M 6 5 /, G'6H O$($ _ 95$,^ 5%_) (4) L
19 25... : K 2(' V( 9k3 p9$ 4: DQ V ` (4) DV 5 V 5 ". 5 " "F`. I() z c 3$) ; 5: 3$) ~ $ V( \(5 V.5 5C( :a(r Q. I() z c F 5 D; "55 I\ 3$) "K " < F` ". (55 Q I() c z c F 5 8 B) 5 ".5 2/5 3$) c 3$ () (z " 3$).5 D; "55 I\ D : 51/ : 3$) K 5 #~ 5 p9$ D; " I\ ( 58/4 8 D ; ( 9$5 64/87 43/8 : 53/6. (z " 5 3$) K I" ; c F" B " $ " EQ 5.9k 58/4 8 D ; $ "B b( 5:P 3$) 5 ; M qv "F`. I( 5."5 9$5 " E(: I\ 5 ; $;5$S ƒo. "5F ( W$) "2$) 1 ('\(4 ("? ; B I I(:5$ ( I D ) 3$) Š2) ` ' "'w YP 2) 5 F\!"v) ; 3$) D;. 5 H=c I(.9$"55 RC g H=c ; #R 2$) S( 5 DQc ; 5 3 D; 5 DM: D 55 RC 5 H=c "55 RC D; ` 9$ W$) W$) $ "2$) " ; Q 5 $5 F OV! P? I( 5$ ; 5.( FV" #;) 4 55 dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. imputation 2. Little & Rubin 3. complete case analysis.9$ SPSS 'w 5 Exclude cases listwise (' u3 #5 I(.4 5. Knol et al
20 6: $6 $;/ %4) 26 DM: I 2) 5 }R R 9(' 5 $ 8 I( 5 ; F 4 \ x" F # "? V( 9k3.9$ D; 5 V( \(5 9('. k" 5@ $ DQ 55 RC I( W$) 5 5 T$M 4 D5 \(V( g b( k(8 "2$) 5@ DM:.9$ (=)FV c 55 RC "2$) S:S: 9" (4 $ 9B$ " = 5 " w5 9(' $ "2$) DM: c 5 #~.9$ 5B 300. k(8 \(V( T$M "2$) S:S: 5 ) I( D; H=c 5 W$) 2$) 1 ( S( (: 1000 S( Y:: I(.55 W$) "2$) " ; I( "W$) 7$ "2$) S:S: 5 900!$) ; FV I(! H=c W$) 5 F; q) \(5 850 \(5 2$) 55 W$) F ; $ # 2$) $ w$ w5 "2$) 5 Y:: 3 " T 2$) $ I( 5 k(8 ; I(.Fˆ "2$) u3 m "2$) 5 k(8 c 5 ; 5..9k 8 $ 9B$ Y$ 5 5 RO` " H=c? I( D; 5 DM: 9(' 5 P "W$) : 5 C F 55 "W$) c 2$) 3$) 5 W$) 2$) S( g: 5 9$ ; p( 9$5 " D; 5@ DM: ; c 5 5 = ; "55 RC D; ` : "2$) 55 \ kt" #T5 NO~ T 4: 5 "2$) W$) 2$) 5 I( V( ; 5; 5 5M g: H=c F: I( 5.( F:) DM: F ; 5 dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. available case analysis 2. Raghunathan
21 27... : " 2$) 5 g: 5 H=c ( 9$ ; $ "2$) q( 9$ wz 4: 5 2$) 5 \ kt" T$M #~ " m I( ; 5 T$M g q(; 2$) 5 S( " 55 W$) 2$) 5 " ; 5 " 7$ q(; " "q( 54 FV I(.( 9$5 2$) 5 \ kt" 9(g 5 : 5 T$M W$) 2$) F ; 5 T$M 5 " F 5 2$) " q( ; 55 D.c \ kt" 55 W$) 2$) 5 " ; 5 55 Z I(.5 1! ( -1 ; : "q( I( ;.55 W$) 2$) 5 " ; 5(=). 5 F 5 g: T$M 9$ 2$) 3$) jk (( H=c? ; 55 F! 8 I(? I( 5 5M k ( 5 I( 54.9k R5 DQ? 5 3$) 5 5 9Tk " ( 4:.!\" : : \!1 9 ; M (T «D;» }R B.T B 2(' F #T5 "-B IRT "# " ) 5 B B 2(' D; <.5 5 Q ; 95 5 m (T.5 C$F " ;!$) 30 $ S( 5 Y:: I(."2$) S:S: N. 9$ " ; 5.5 $ 9$ 55 K 3$).5 1 g: 2$) ( 5 "B.5 74 = 0/ W$) "2$) (\3$) 9Tk 5! "2$) 5 : 1 " I(. H=c.( 2(' W$) 5 H=c 9 ; ( (z " 5 5:P 3$) 9M: $ B " ( H=c 5 I(.55 F!.5 5 3$) K 9M: c () $ Y4 F H=c : 5 W$) 5 5 (T 9k 8Q5 V" 5 5:P 5: 3$) -3!:.5! b( dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd.9$ SPSS 'w 5 Exclude cases pairwise (' u3 #5 I(.1
22 6: $6 $;/ %4) 28 ( \3$) 5 W$) 5 B9 4 "v( k(8 ^(` c : 55 W$) g 5 " ; ("2$) (\3$) M k(8.9( 9$5-3!: I( F: 4: 5 ' "( $ w: OR ; ( 5 W$) 5 H=c ( ; H=c? ; 9$ m 5 D; k(8 5! 2"; : "( < 5 : ) 5 786' #~.5 L 3 $ " 5 9@. I( 9 Z $ F q) g S( D; 2"; " 3$) 5 5 H=c 5 Q 4: 5 "( 5 : ( " 2"; Y4 " 95 "B " ; 9Tk V1; 5 (g: S( " ; "B $. k" 5 DM: 5V( 1 3$) 5 5 H=c nc 5 D; ` ; 9k V" 54 5 DM: 5V( 1 D; $ 9B$ 5.( F(" ) C 3$) DV! Dc 5 9$ 5 g 55 DM: " "2$) 5@ DM: " D; "W$) (C" = T $ S( ; V" $ m I(.; 5@ $ $ "2$) 5 9 OV! ' 5: NO; 3$) 9M: c F H=c 3$) K 9$ Z I(. '1 k 3$) K V( \ F 786' 5 g 5B "2$).5 S; 21 I( 8 :^Q5 ; " dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd 1. van der Heijden
23 29... : G Azar, B. (2002). Finding a solution for missing data. Monitor on Psychology, 33 (7), 70. Bhaskaran, K.; & Smeeth, L. (2014). What is the difference between missing completely at random and missing at random? International Journal of Epidemiology, 43 (4), Bodner, T. E. (2006). Missing data: Prevalence and reporting practices. Psychological Reports, 99, Cao, W.; Tsiatis, A. A.; & Davidian, M. (2009). Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data. Biometrika, 96, Dillman, D. A.; Eltinge, J. L.; Groves, R. M.; & Little, R. J. (2002). Survey nonresponse in design, data collection, and analysis. Survey nonresponse, Enders, C. K. (2003). Using the expectation maximization algorithm to estimate coefficient alpha for scales with item-level missing data. Psychological methods, 8 (3), 322. Fowler Jr, F. J. (2013). Survey research methods. Sage publications. Graham, J. W.; & Coffman, D. L. (2012). Structural equation modeling with missing data. Handbook of structural equation modeling, Groves, R. M.; & Couper, M. P. (2012). Nonresponse in household interview surveys. John Wiley & Sons. Groves, R. M.; Fowler Jr, F. J.; Couper, M. P.; Lepkowski, J. M.; Singer, E.; & Tourangeau, R. (2011). Survey methodology (Vol. 561). John Wiley & Sons. Hox, J.; De Leeuw, E. D.; Couper, M. P.; Groves, R. M.; De Heer, W.; Kuusela, V.; & Belak, E. (2002). The influence of interviewers attitude and behaviour on household survey nonresponse: An international comparison. In: R. M. Groves, D. A. Dillman, J. L. Eltinge, & R.J.A. Little (Eds). Survey nonresponse. New York: Wiley, pp Knol, M. J.; Janssen, K. J.; Donders, A. R. T.; Egberts, A. C.; Heerdink, E. R.; Grobbee, D. E.;... & Geerlings, M. I. (2010). Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example. Journal of Clinical Epidemiology, 63 (7),
24 6: $6 $;/ %4) 30 Kromrey, J. D.; & Hines, C. V. (1994). Nonrandomly missing data in multiple regression: An empirical comparison of common missing-data treatments. Educational & Psychological Measurement, 54 (3), Little, R. J.; & Rubin, D. B. (2014). Statistical analysis with missing data. John Wiley & Sons. Mcdonald, R. A.; Thurston, P. W.; & Nelson, M. R. (2000). A Monte Carlo study of missing item methods. Organizational Research Methods, 3 (1), Peugh, J. L.; & Enders, C. K. (2004). Missing data in educational research: A review of reporting practices and suggestions for improvement. Review of Educational Research, 74 (4), Raghunathan, T. E. (2004). What do we do with missing data? Some options for analysis of incomplete data. Annu. Rev. Public Health, 25, Roth, P. L. (1994). Missing data: A conceptual review for applied psychologists. Personnel Psychology, 47 (3), Seaman, S.; Galati, J.; Jackson, D.; & Carlin, J. (2013). What Is Meant by" Missing at Random"? Statistical Science, Tang, G.; Little, R. J.; & Raghunathan, T. E. (2003). Analysis of multivariate missing data with nonignorable nonresponse. Biometrika, Tourangeau, R.; Rips, L. J.; & Rasinski, K. (2000). The psychology of survey response. Cambridge University Press. Van der Heijden, G. J.; Donders, A. R. T.; Stijnen, T.; & Moons, K. G. (2006). Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example. Journal of Clinical Epidemiology, 59 (10),
An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Observational Studies
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