id	sid	tid	token	lemma	pos
bk128912m57	1	1	in	in	ADP
bk128912m57	1	2	the	the	DET
bk128912m57	1	3	study	study	NOUN
bk128912m57	1	4	,	,	PUNCT
bk128912m57	1	5	i	i	PRON
bk128912m57	1	6	consider	consider	VERB
bk128912m57	1	7	a	a	DET
bk128912m57	1	8	simple	simple	ADJ
bk128912m57	1	9	moderated	moderated	ADJ
bk128912m57	1	10	multiple	multiple	ADJ
bk128912m57	1	11	regression	regression	NOUN
bk128912m57	1	12	(	(	PUNCT
bk128912m57	1	13	mmr	mmr	PROPN
bk128912m57	1	14	)	)	PUNCT
bk128912m57	1	15	model	model	NOUN
bk128912m57	1	16	,	,	PUNCT
bk128912m57	1	17	where	where	SCONJ
bk128912m57	1	18	the	the	DET
bk128912m57	1	19	effect	effect	NOUN
bk128912m57	1	20	of	of	ADP
bk128912m57	1	21	predictor	predictor	NOUN
bk128912m57	1	22	x	x	PUNCT
bk128912m57	1	23	on	on	ADP
bk128912m57	1	24	the	the	DET
bk128912m57	1	25	outcome	outcome	NOUN
bk128912m57	1	26	y	y	PROPN
bk128912m57	1	27	is	be	AUX
bk128912m57	1	28	moderated	moderate	VERB
bk128912m57	1	29	by	by	ADP
bk128912m57	1	30	a	a	DET
bk128912m57	1	31	moderator	moderator	NOUN
bk128912m57	1	32	u.	u.	PROPN
bk128912m57	2	1	my	my	PRON
bk128912m57	2	2	primary	primary	ADJ
bk128912m57	2	3	interest	interest	NOUN
bk128912m57	2	4	is	be	AUX
bk128912m57	2	5	to	to	PART
bk128912m57	2	6	find	find	VERB
bk128912m57	2	7	ways	way	NOUN
bk128912m57	2	8	of	of	ADP
bk128912m57	2	9	estimating	estimate	VERB
bk128912m57	2	10	and	and	CCONJ
bk128912m57	2	11	testing	test	VERB
bk128912m57	2	12	the	the	DET
bk128912m57	2	13	moderation	moderation	NOUN
bk128912m57	2	14	effect	effect	NOUN
bk128912m57	2	15	with	with	ADP
bk128912m57	2	16	the	the	DET
bk128912m57	2	17	existence	existence	NOUN
bk128912m57	2	18	of	of	ADP
bk128912m57	2	19	missing	miss	VERB
bk128912m57	2	20	data	datum	NOUN
bk128912m57	2	21	.	.	PUNCT
bk128912m57	3	1	i	i	PRON
bk128912m57	3	2	mainly	mainly	ADV
bk128912m57	3	3	focus	focus	VERB
bk128912m57	3	4	on	on	ADP
bk128912m57	3	5	cases	case	NOUN
bk128912m57	3	6	when	when	SCONJ
bk128912m57	3	7	x	x	PUNCT
bk128912m57	3	8	and/or	and/or	CCONJ
bk128912m57	3	9	y	y	PROPN
bk128912m57	3	10	are	be	AUX
bk128912m57	3	11	missing	miss	VERB
bk128912m57	3	12	completely	completely	ADV
bk128912m57	3	13	at	at	ADP
bk128912m57	3	14	random	random	ADJ
bk128912m57	3	15	(	(	PUNCT
bk128912m57	3	16	mcar	mcar	PROPN
bk128912m57	3	17	)	)	PUNCT
bk128912m57	3	18	,	,	PUNCT
bk128912m57	3	19	missing	miss	VERB
bk128912m57	3	20	at	at	ADP
bk128912m57	3	21	random	random	ADJ
bk128912m57	3	22	(	(	PUNCT
bk128912m57	3	23	mar	mar	PROPN
bk128912m57	3	24	)	)	PUNCT
bk128912m57	3	25	or	or	CCONJ
bk128912m57	3	26	missing	miss	VERB
bk128912m57	3	27	depending	depend	VERB
bk128912m57	3	28	on	on	ADP
bk128912m57	3	29	auxiliary	auxiliary	ADJ
bk128912m57	3	30	variables	variable	NOUN
bk128912m57	3	31	(	(	PUNCT
bk128912m57	3	32	missing	miss	VERB
bk128912m57	3	33	not	not	PART
bk128912m57	3	34	at	at	ADP
bk128912m57	3	35	random	random	ADJ
bk128912m57	3	36	;	;	PUNCT
bk128912m57	3	37	denoted	denote	VERB
bk128912m57	3	38	av	av	PROPN
bk128912m57	3	39	-	-	PUNCT
bk128912m57	3	40	mnar	mnar	PROPN
bk128912m57	3	41	)	)	PUNCT
bk128912m57	3	42	.	.	PUNCT
bk128912m57	4	1	four	four	NUM
bk128912m57	4	2	methods	method	NOUN
bk128912m57	4	3	are	be	AUX
bk128912m57	4	4	proposed	propose	VERB
bk128912m57	4	5	and	and	CCONJ
bk128912m57	4	6	compared	compare	VERB
bk128912m57	4	7	:	:	PUNCT
bk128912m57	4	8	(	(	PUNCT
bk128912m57	4	9	1	1	X
bk128912m57	4	10	)	)	PUNCT
bk128912m57	4	11	listwise	listwise	NOUN
bk128912m57	4	12	deletion	deletion	NOUN
bk128912m57	4	13	;	;	PUNCT
bk128912m57	4	14	(	(	PUNCT
bk128912m57	4	15	2	2	X
bk128912m57	4	16	)	)	PUNCT
bk128912m57	4	17	normal	normal	ADJ
bk128912m57	4	18	-	-	PUNCT
bk128912m57	4	19	distribution	distribution	NOUN
bk128912m57	4	20	-	-	PUNCT
bk128912m57	4	21	based	base	VERB
bk128912m57	4	22	maximum	maximum	ADJ
bk128912m57	4	23	likelihood	likelihood	NOUN
bk128912m57	4	24	estimation	estimation	NOUN
bk128912m57	4	25	(	(	PUNCT
bk128912m57	4	26	nml	nml	PROPN
bk128912m57	4	27	)	)	PUNCT
bk128912m57	4	28	;	;	PUNCT
bk128912m57	4	29	(	(	PUNCT
bk128912m57	4	30	3	3	X
bk128912m57	4	31	)	)	PUNCT
bk128912m57	4	32	normal	normal	ADJ
bk128912m57	4	33	-	-	PUNCT
bk128912m57	4	34	distribution	distribution	NOUN
bk128912m57	4	35	-	-	PUNCT
bk128912m57	4	36	based	base	VERB
bk128912m57	4	37	multiple	multiple	ADJ
bk128912m57	4	38	imputation	imputation	NOUN
bk128912m57	4	39	(	(	PUNCT
bk128912m57	4	40	nmi	nmi	PROPN
bk128912m57	4	41	)	)	PUNCT
bk128912m57	4	42	;	;	PUNCT
bk128912m57	4	43	and	and	CCONJ
bk128912m57	4	44	(	(	PUNCT
bk128912m57	4	45	4	4	X
bk128912m57	4	46	)	)	PUNCT
bk128912m57	4	47	bayesian	bayesian	ADJ
bk128912m57	4	48	estimation	estimation	NOUN
bk128912m57	4	49	(	(	PUNCT
bk128912m57	4	50	be	be	AUX
bk128912m57	4	51	)	)	PUNCT
bk128912m57	4	52	.	.	PUNCT
bk128912m57	5	1	results	result	NOUN
bk128912m57	5	2	from	from	ADP
bk128912m57	5	3	simulation	simulation	NOUN
bk128912m57	5	4	studies	study	NOUN
bk128912m57	5	5	show	show	VERB
bk128912m57	5	6	that	that	SCONJ
bk128912m57	5	7	the	the	DET
bk128912m57	5	8	proposed	propose	VERB
bk128912m57	5	9	methods	method	NOUN
bk128912m57	5	10	had	have	VERB
bk128912m57	5	11	different	different	ADJ
bk128912m57	5	12	relative	relative	ADJ
bk128912m57	5	13	performance	performance	NOUN
bk128912m57	5	14	depending	depend	VERB
bk128912m57	5	15	on	on	ADP
bk128912m57	5	16	various	various	ADJ
bk128912m57	5	17	factors	factor	NOUN
bk128912m57	5	18	.	.	PUNCT
bk128912m57	6	1	the	the	DET
bk128912m57	6	2	factors	factor	NOUN
bk128912m57	6	3	are	be	AUX
bk128912m57	6	4	missing	miss	VERB
bk128912m57	6	5	data	datum	NOUN
bk128912m57	6	6	mechanisms	mechanism	NOUN
bk128912m57	6	7	,	,	PUNCT
bk128912m57	6	8	population	population	NOUN
bk128912m57	6	9	moderation	moderation	NOUN
bk128912m57	6	10	effect	effect	NOUN
bk128912m57	6	11	sizes	size	NOUN
bk128912m57	6	12	,	,	PUNCT
bk128912m57	6	13	sample	sample	NOUN
bk128912m57	6	14	sizes	size	NOUN
bk128912m57	6	15	,	,	PUNCT
bk128912m57	6	16	missing	miss	VERB
bk128912m57	6	17	data	data	NOUN
bk128912m57	6	18	proportions	proportion	NOUN
bk128912m57	6	19	,	,	PUNCT
bk128912m57	6	20	and	and	CCONJ
bk128912m57	6	21	distributions	distribution	NOUN
bk128912m57	6	22	of	of	ADP
bk128912m57	6	23	predictor	predictor	PROPN
bk128912m57	6	24	x.	x.	PROPN
bk128912m57	6	25	influence	influence	PROPN
bk128912m57	6	26	of	of	ADP
bk128912m57	6	27	adding	add	VERB
bk128912m57	6	28	auxiliary	auxiliary	ADJ
bk128912m57	6	29	variables	variable	NOUN
bk128912m57	6	30	is	be	AUX
bk128912m57	6	31	also	also	ADV
bk128912m57	6	32	discussed	discuss	VERB
bk128912m57	6	33	in	in	ADP
bk128912m57	6	34	terms	term	NOUN
bk128912m57	6	35	of	of	ADP
bk128912m57	6	36	estimation	estimation	NOUN
bk128912m57	6	37	accuracy	accuracy	NOUN
bk128912m57	6	38	for	for	ADP
bk128912m57	6	39	nml	nml	PROPN
bk128912m57	6	40	and	and	CCONJ
bk128912m57	6	41	nmi	nmi	PROPN
bk128912m57	6	42	.	.	PUNCT