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2016-10-17		|		UC	Berkeley	 Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	 81	
Addi(onal Slides
Publica(on Bias
Trends…
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
82
P-hacking
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
83
Negligent/sub-
standard Science
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
84
Cochrane Reviews
2016-10-17		|		UC	Berkeley	
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85	
hkp://community.cochrane.org/cochrane-reviews	
“We	gather	and	
summarize	the	best	
evidence	from	research	
to	help	you	make	
informed	choices	about	
treatment...	
	
Cochrane	contributors	-	
37,000	from	more	than	
130	countries	-	work	
together	to	produce	
credible,	accessible	
health	informa)on	that	
is	free	from	commercial	
sponsorship	and	other	
conflicts	of	interest.”
Transparent Repor(ng
& Systema(c Reviews
• “Systema)c	reviews	seek	to	collate	all	evidence	that	fits	pre-specified	
eligibility	criteria	in	order	to	address	a	specific	research	ques)on	
• Systema)c	reviews	aim	to	minimize	bias	by	using	explicit,	systema)c	
methods	
• The	Cochrane	Collabora)on	prepares,	maintains	and	promotes	systema)c	
reviews	to	inform	healthcare	decisions:	Cochrane	Reviews”	
2016-10-17		|		UC	Berkeley	
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86	
hkp://
community.cochrane.or
g/about-us/evidence-
based-health-care
2016-10-17		|		UC	Berkeley	 Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	 87	
Details on CONSORT Checklist
CONSORT Checklist
Introduc(on
TITLE	&	ABSTRACT	
•  1a.	Iden)fica)on	as	a	randomised	trial	in	the	)tle	
•  1b.	Structured	summary	of	trial	design,	methods,	results,	and	conclusions	(for	
specific	guidance	see	CONSORT	for	abstracts)	
BACKGROUND	&	OBJECTIVES	
•  2a.	Scien)fic	background	and	explana)on	of	ra)onale	
•  2b.	Specific	objec)ves	or	hypotheses	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
88
CONSORT Checklist:
Methods
TRIAL	DESIGN	
•  3a.	Descrip)on	of	trial	design	(such	as	parallel,	factorial)	including	alloca)on	
ra)o	
•  3b.	Important	changes	to	methods	ajer	trial	commencement	(such	as	
eligibility	criteria),	with	reasons	
PARTICIPANTS	
•  4a.	Eligibility	criteria	for	par)cipants	
•  5a.	Se{ngs	and	loca)ons	where	the	data	were	collected	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
89
CONSORT Checklist:
Methods
INTERVENTIONS	
•  5.	The	interven)ons	for	each	group	with	sufficient	details	to	allow	replica)on,	
including	how	and	when	they	were	actually	administered		
OUTCOMES	
•  6a.	Completely	defined	pre-specified	primary	and	secondary	outcome	
measures,	including	how	and	when	they	were	assessed	
•  6b.	Any	changes	to	trial	outcomes	ajer	the	trial	commenced,	with	reasons	
SAMPLE	SIZE	
•  7a.	How	sample	size	was	determined	
•  7b.	When	applicable,	explana)on	of	any	interim	analyses	and	stopping	
guidelines	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
90
CONSORT Checklist:
Methods
RANDOMIZATION:	SEQUENCE	GENERATION	
•  8a.	Method	used	to	generate	the	random	alloca)on	sequence	
•  8b.	Type	of	randomisa)on;	details	of	any	restric)on	(such	as	blocking	and	
block	size)	
RANDOMIZATION:	ALLOCATION	CONCEALMENT	
•  9.	Mechanism	used	to	implement	the	random	alloca)on	sequence	(such	as	
sequen)ally	numbered	containers),	describing	any	steps	taken	to	conceal	the	
sequence	un)l	interven)ons	were	assigned		
RANDOMIZATION:	IMPLEMENTATION	
•  10.	Who	generated	the	random	alloca)on	sequence,	who	enrolled	
par)cipants,	and	who	assigned	par)cipants	to	interven)ons		
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
91
CONSORT Checklist:
Methods
BLINDING	
•  11a.	If	done,	who	was	blinded	ajer	assignment	to	interven)ons	(for	example,	
par)cipants,	care	providers,	those	assessing	outcomes)	and	how	
•  11b.	If	relevant,	descrip)on	of	the	similarity	of	interven)ons	
STATISTICAL	METHODS	
•  12a.	Sta)s)cal	methods	used	to	compare	groups	for	primary	and	secondary	
outcomes	
•  12b.	Methods	for	addi)onal	analyses,	such	as	subgroup	analyses	and	adjusted	
analyses	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
92
CONSORT Checklist:
Results
PARTICIPANT	FLOW	
(DIAGRAM	
RECOMMENDED)	
•  13a.	For	each	group,	the	
numbers	of	par)cipants	
who	were	randomly	
assigned,	received	
intended	treatment,	and	
were	analysed	for	the	
primary	outcome	
•  13b.	For	each	group,	
losses	and	exclusions	
ajer	randomisa)on,	
together	with	reasons	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
93	
CONSORT	2010	Flow	Diagram	
Assessed for eligibility (n= )
Excluded (n= )
¨			Not meeting inclusion criteria (n= )
¨			Declined to participate (n= )
¨			Other reasons (n= )
Analysed (n= )
¨	Excluded from analysis (give reasons) (n= )	
Lost to follow-up (give reasons) (n= )
Discontinued intervention (give reasons) (n= )
Allocated to intervention (n= )
¨	Received allocated intervention (n= )	
¨	Did not receive allocated intervention (give
reasons) (n= )	
Lost to follow-up (give reasons) (n= )
Discontinued intervention (give reasons) (n= )
Allocated to intervention (n= )
¨	Received allocated intervention (n= )	
¨	Did not receive allocated intervention (give
reasons) (n= )	
Analysed (n= )
¨	Excluded from analysis (give reasons) (n= )	
	
Allocation
Analysis
Follow-Up
Randomized (n= )
Enrollment
CONSORT Checklist:
Results
RECRUITMENT	
•  14a.	Dates	defining	the	periods	of	recruitment	and	follow-up	
•  14b.	Why	the	trial	ended	or	was	stopped	
	
BASELINE	DATA	
•  15.	A	table	showing	baseline	demographic	and	clinical	characteris)cs	for	each	
group	
NUMBER	ANALYZED	
•  16.	For	each	group,	number	of	par)cipants	(denominator)	included	in	each	
analysis	and	whether	the	analysis	was	by	original	assigned	groups	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
94
CONSORT Checklist:
Results
OUTCOMES	AND	ESTIMATION	
•  17a.	For	each	primary	and	secondary	outcome,	results	for	each	group,	and	the	
es)mated	effect	size	and	its	precision	(such	as	95%	confidence	interval)	
•  17b.	For	binary	outcomes,	presenta)on	of	both	absolute	and	rela)ve	effect	
sizes	is	recommended	
ANCILLARY	ANALYSES	
•  18.	Results	of	any	other	analyses	performed,	including	subgroup	analyses	and	
adjusted	analyses,	dis)nguishing	pre-specified	from	exploratory	
HARMS	
•  All	important	harms	or	unintended	effects	in	each	group		
(for	specific	guidance	see	CONSORT	for	harms)	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
95
CONSORT Checklist:
Discussion
LIMITATIONS	
•  20.	Trial	limita)ons,	addressing	sources	of	poten)al	bias,	imprecision,	and,	if	
relevant,	mul)plicity	of	analyses	
GENERALIZABILITY	
•  21.	Generalizability	(external	validity,	applicability)	of	the	trial	findings	
INTERPRETATION	
•  22.	Interpreta)on	consistent	with	results,	balancing	benefits	and	harms,	and	
considering	other	relevant	evidence	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
96
CONSORT Checklist:
Other Informa(on
REGISTRATION	
•  23.	Registra)on	number	and	name	of	trial	registry	
PROTOCOL	
•  24.	Where	the	full	trial	protocol	can	be	accessed,	if	available	
FUNDING	
•  25.	Sources	of	funding	and	other	support	(such	as	supply	of	drugs),	role	of	
funders	
2016-10-17		|		UC	Berkeley	
Alasdair	Cohen		|		Lecture	for	Publich	Health	250B	
97

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5.3.2 sufficient cause em5.3.2 sufficient cause em
5.3.2 sufficient cause em
 
5.3.1 causal em
5.3.1 causal em5.3.1 causal em
5.3.1 causal em
 
5.2.3 dags for selection bias
5.2.3 dags for selection bias5.2.3 dags for selection bias
5.2.3 dags for selection bias
 
5.2.2 dags for confounding
5.2.2 dags for confounding5.2.2 dags for confounding
5.2.2 dags for confounding
 
5.1.2 counterfactual framework
5.1.2 counterfactual framework5.1.2 counterfactual framework
5.1.2 counterfactual framework
 
5.1.1 sufficient component cause model
5.1.1 sufficient component cause model5.1.1 sufficient component cause model
5.1.1 sufficient component cause model
 
5.2.1 dags
5.2.1 dags5.2.1 dags
5.2.1 dags
 
4.3.2. controlling confounding stratification
4.3.2. controlling confounding stratification4.3.2. controlling confounding stratification
4.3.2. controlling confounding stratification
 
4.3.1. controlling confounding matching
4.3.1. controlling confounding matching4.3.1. controlling confounding matching
4.3.1. controlling confounding matching
 
4.2.3. confounding collapsability
4.2.3. confounding collapsability4.2.3. confounding collapsability
4.2.3. confounding collapsability
 
4.2.2. confounding classical approach
4.2.2. confounding classical approach4.2.2. confounding classical approach
4.2.2. confounding classical approach
 
4.2.1. confounding mixing of effects
4.2.1. confounding mixing of effects4.2.1. confounding mixing of effects
4.2.1. confounding mixing of effects
 
4.1. introduction
4.1. introduction4.1. introduction
4.1. introduction
 
4 Threats to validity from confounding bias and effect modification
4 Threats to validity from confounding bias and effect modification4 Threats to validity from confounding bias and effect modification
4 Threats to validity from confounding bias and effect modification
 
6.5 strengths and challenges
6.5 strengths and challenges6.5 strengths and challenges
6.5 strengths and challenges
 
6.7 summaries
6.7 summaries6.7 summaries
6.7 summaries
 

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