causal relationships, bias, and research designs professor anthony digirolamo
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Causal relationships, bias, and research designs
Professor Anthony DiGirolamo
Causal Relationships
Causal RelationshipsSufficient Cause
Causal RelationshipsSufficient Cause
Precedes diseases, factor always present with disease
Causal RelationshipsSufficient Cause
Precedes diseases, factor always present with disease
Necessary Cause
Causal RelationshipsSufficient Cause
Precedes diseases, factor always present with disease
Necessary CauseFactor must be present for disease, but factor
can be present without developing disease
Causal RelationshipsSufficient Cause
Precedes diseases, factor always present with disease
Necessary CauseFactor must be present for disease, but factor
can be present without developing diseaseRisk Factor
Causal RelationshipsSufficient Cause
Precedes diseases, factor always present with disease
Necessary CauseFactor must be present for disease, but factor
can be present without developing diseaseRisk Factor
An exposure, behavior, or attribute that, if present, clearly influences the probability of disease
Determining Cause and Effect
Determining Cause and EffectMill’s Cannons
Determining Cause and EffectMill’s Cannons
Strength Association shows a large difference
Determining Cause and EffectMill’s Cannons
Strength Association shows a large difference
Consistency Association is always present with the disease
Determining Cause and EffectMill’s Cannons
Strength Association shows a large difference
Consistency Association is always present with the disease
Specificity No disease if the factor isn’t present
Determining Cause and EffectMill’s Cannons
Strength Association shows a large difference
Consistency Association is always present with the disease
Specificity No disease if the factor isn’t present
Biological Plausibility Fits the natural history of the disease
Common PitfallsWhat is bias?
Common PitfallsWhat is bias?
An event that produces deviations that shift data in a particular direction (skew your data)
Common PitfallsWhat is bias?
An event that produces deviations that shift data in a particular direction (skew your data)
Common Types
Common PitfallsWhat is bias?
An event that produces deviations that shift data in a particular direction (skew your data)
Common TypesAssembly bias – characteristics of a group are
not evenly distributed
Common PitfallsWhat is bias?
An event that produces deviations that shift data in a particular direction (skew your data)
Common TypesAssembly bias – characteristics of a group are
not evenly distributedSelection bias – participants allowed to select
which part of the study they are in
Common PitfallsWhat is bias?
An event that produces deviations that shift data in a particular direction (skew your data)
Common TypesAssembly bias – characteristics of a group are
not evenly distributedSelection bias – participants allowed to select
which part of the study they are inDetection bias – failure to detect true cause of
disease
Common PitfallsWhat is bias?
An event that produces deviations that shift data in a particular direction (skew your data)
Common TypesAssembly bias – characteristics of a group are
not evenly distributedSelection bias – participants allowed to select
which part of the study they are inDetection bias – failure to detect true cause of
diseaseMeasurement bias –variations due to
instrumentation or user error
Common PitfallsAdditional concerns when doing research…?
Common PitfallsAdditional concerns when doing research…?
Random error
Common PitfallsAdditional concerns when doing research…?
Random errorConfounding
Common PitfallsAdditional concerns when doing research…?
Random errorConfoundingSynergism
Research DesignAll research is descriptive, and results are
directly related to the data assembled
Research DesignAll research is descriptive, and results are
directly related to the data assembledWhat is a hypothesis ?
Research DesignAll research is descriptive, and results are
directly related to the data assembledWhat is a hypothesis ?
An “educated guess” about the relationship that exists in an observed phenomenon
Research DesignAll research is descriptive, and results are
directly related to the data assembledWhat is a hypothesis ?
An “educated guess” about the relationship that exists in an observed phenomenon
Not always right; often need to re-test to truly discern relationship
Research DesignAll research is descriptive, and results are
directly related to the data assembledWhat is a hypothesis ?
An “educated guess” about the relationship that exists in an observed phenomenon
Not always right; often need to re-test to truly discern relationship It’s called RE-SEARCH for a reason ! : )
Research Design4 Key Factors of Research Designs
Research Design4 Key Factors of Research Designs
Enable comparison of a variable for two or more groups at a specified time
Research Design4 Key Factors of Research Designs
Enable comparison of a variable for two or more groups at a specified time
Comparison must be quantified in absolute or relative terms
Research Design4 Key Factors of Research Designs
Enable comparison of a variable for two or more groups at a specified time
Comparison must be quantified in absolute or relative terms
Allow determination of the temporal sequence (when and how the factor and disease occur)
Research Design4 Key Factors of Research Designs
Enable comparison of a variable for two or more groups at a specified time
Comparison must be quantified in absolute or relative terms
Allow determination of the temporal sequence (when and how the factor and disease occur)
Minimize bias, confounding, and other outside elements that may skew from true results
Research DesignsDesigns for Generating Hypotheses
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Surveys
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Surveys Quick, cost-effective studies done of a population at
a certain point in time (calls, interviews, appointments, etc)
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Surveys Quick, cost-effective studies done of a population at
a certain point in time (calls, interviews, appointments, etc)
Useful in determining prevalent risk factors in a population
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Surveys Quick, cost-effective studies done of a population at
a certain point in time (calls, interviews, appointments, etc)
Useful in determining prevalent risk factors in a population
Surveys sometimes have low response rates
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Ecological Studies
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Ecological Studies Relate the frequency of one characteristic
(smoking) and an outcome (lung cancer) occurring in a geographical area
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Ecological Studies Relate the frequency of one characteristic
(smoking) and an outcome (lung cancer) occurring in a geographical area
Downside is too many other factors and temporal issues may be overlooked or incorrectly identified
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Ecological Studies Relate the frequency of one characteristic
(smoking) and an outcome (lung cancer) occurring in a geographical area
Downside is too many other factors and temporal issues may be overlooked or incorrectly identified
Longitudinal Ecological Studies
Research DesignsDesigns for Generating Hypotheses
Cross-Sectional Ecological Studies Relate the frequency of one characteristic
(smoking) and an outcome (lung cancer) occurring in a geographical area
Downside is too many other factors and temporal issues may be overlooked or incorrectly identified
Longitudinal Ecological Studies Long-term surveillance or frequent cross-sectional
surveys to measure trends in disease rates over many years
Research DesignsDesigns for Generating or Testing
Hypotheses
Research DesignsDesigns for Generating or Testing
HypothesesCohort Studies
Research DesignsDesigns for Generating or Testing
HypothesesCohort Studies
Compares two groups of clearly defined individuals, randomly selected
Research DesignsDesigns for Generating or Testing
HypothesesCohort Studies
Compares two groups of clearly defined individuals, randomly selected
Observations made to examine if one group develops a condition with a risk factor, the other without
Research DesignsDesigns for Generating or Testing
HypothesesProspective vs. Retrospective Cohort Studies
Research DesignsDesigns for Generating or Testing
HypothesesProspective vs. Retrospective Cohort Studies
Prospective cohorts are done at present time, baseline data recorded and then observed over time
Research DesignsDesigns for Generating or Testing
HypothesesProspective vs. Retrospective Cohort Studies
Prospective cohorts are done at present time, baseline data recorded and then observed over time
Retrospective cohorts look back in time to a risk group and follow members in a current day scenario to see what conditions are now prevalent
Research DesignsDesigns for Generating or Testing Hypotheses
Prospective vs. Retrospective Cohort Studies Prospective cohorts are done at present time,
baseline data recorded and then observed over time Advantages are control of standardized procedures
and diagnosis, estimates of risk generated are true, many different disease outcomes may be studied at once
Disadvantages are high costs, loss of follow-up, long wait for final results
Retrospective cohorts look back in time to a risk group and follow members in a current day scenario to see what conditions are now prevalent
Research DesignsDesigns for Generating or Testing Hypotheses
Prospective vs. Retrospective Cohort Studies Prospective cohorts are done at present time, baseline
data recorded and then observed over time Advantages are control of standardized procedures and
diagnosis, estimates of risk generated are true, many different disease outcomes may be studied at once
Disadvantages are high costs, loss of follow-up, long wait for final results
Retrospective cohorts look back in time to a risk group and follow members in a current day scenario to see what conditions are now prevalent Good to estimate absolute risk, but lacks ability to
control data collection and standardization
Research DesignsDesigns for Testing Hypotheses
Research DesignsDesigns for Testing Hypotheses
Randomized Controlled Clinical Trials (RCCT)
Research DesignsDesigns for Testing Hypotheses
Randomized Controlled Clinical Trials (RCCT) Patients placed into two groups, one receiving a
treatment the other a placebo (usually a therapeutic treatment)
Use of “blinding” in trials ?
Research DesignsDesigns for Testing Hypotheses
Randomized Controlled Clinical Trials (RCCT) Patients placed into two groups, one receiving a
treatment the other a placebo (usually a therapeutic treatment)
Use of “blinding” in trials ? Patients are unaware of which group they are in
(single), those dosing the patients also do not know (double)
Key is that both groups must be treated equally
Research DesignsDesigns for Testing Hypotheses
Randomized Controlled Clinical Trials (RCCT) Patients placed into two groups, one receiving a
treatment the other a placebo (usually a therapeutic treatment)
Use of “blinding” in trials ? Patients are unaware of which group they are in
(single), those dosing the patients also do not know (double)
Key is that both groups must be treated equally
Randomized Controlled Field Trials (RCFT)
Research DesignsDesigns for Testing Hypotheses
Randomized Controlled Clinical Trials (RCCT) Patients placed into two groups, one receiving a
treatment the other a placebo (usually a therapeutic treatment)
Use of “blinding” in trials ? Patients are unaware of which group they are in (single),
those dosing the patients also do not know (double) Key is that both groups must be treated equally
Randomized Controlled Field Trials (RCFT) Focuses on using a preventative measure, rather than a
therapeutical one (RCCT)
Well Done!!