Experimental Design Flashcards
Negative Control
Group added where you know the outcome but the IV will not affect the group
- Often considered the best control
- Helps guard against epiphenomenon (result that accompanies another, but has no causal influence itself or what not caused by the experiment) – an observed effect in this control means there’s something else influencing the DV.
- Known to give a - result.
Positive Control
Group added to a design where you know what the outcome will be, and the outcome is expected to move in the direction you think the IV should move it
- Used to ensure the experimental set up is working
- Provides comfort about the effects of the IV
- Similar to the actual experimental test, but which is known to give a + result
Vehicle Control
Injectate or pill without the substance (placebo) Contains everything you are administering except the level of IV
Sham Control
Generally associated with a surgical procedure, in while a mock surgery is performed. Form of procedural control.
Procedural control
Running the same procedure without the active intervention.
*One group has one procedure, other group has slightly altered procedure w/o the IV
Repeated measures
Use the subject as their own control, or alternatively using one side of the animal as a control for another animal
*This method can sometimes introduce possible learning curves/practice effect
Hypothesis driven
Research in which a specific hypothesis is laid out upfront and then tested prospectively
Prospective study
Hypothesis laid out and research is analyzed based off data obtained in the future, after application of the IV.
Retrospective studies
Assess effect of an IV after the fact.
Discovery research
formulates the basis for hypothesis driven research
*Generates Ho
Clinical Trial
study of a group of individuals that have something is common and who are assessed as they move forward in time (Prospective study)
**Usually assessed more than once (Repeated measure).
Clinical Trial
A study on patients (human) that is prospective, and tests a very SPECIFIC question- generally about a drug or specific intervention.
*Is the most rigorous (from control perspective)
Cohort study
study of a group of individuals that share something in common, and who are assessed as they move forward in time (prospective)
- Greater work load
- Over a time period
- Usually repeated measure.
Cross-sectional study
Similar to a cohort study, except that all the measures are taken at the same time (one point in time, usually present) “snap-shot” of your test population at specific time point.
- Retrospective study
- Prevalence study
Case-control study
Similar to cross-sectional study, except that these are looking at various past times– identifies one group with variable, one without said variable, and assesses their PAST habits/lifestyles in order to formulate an association.
- Retrospective
- Past focused
Ethnographic research
Study of human behavior in natural context, involving OBSERVATION of behavior in physical setting
Explanatory Research
Where the experimenter seeks to determine cause and effect. NOT and association.
*Most studies look at associations between IV and DV, not cause and effect
Historical Research
The systematic collection and evaluation of data relation to past occurrences in order to describe causes, effects, and trends of those events that may help explain present events and anticipate future events
Quasi-experiment
*Empirical study
used to estimate the causal impact of an intervention on a target population.
*Share many elements with traditional experimental design, but lack the element of random assignment to control or treatment
*The investigator does not have control over the assignment of the IV as true in other experimental design – but is not random, some control through other methods (ie, eligability cut-off)
Prevention Trials
Look for better ways to prevent disease in people who do not have the disease
*Outcome research
Screening Trials
Test the best way to detect a certain disease of condition,
Diagnostic Trial
Conducted to find better tests or procedures for diagnosing a particular disease/condition
Increases diagnostic value
Treatment Trial
tests experimental treatments, new combinations of drugs, or new approaches to surgery/radiation therapy
Quality of Life Trials
(Supportive Care trial) Explores ways to improve comfort and quality of life for individuals with chronic/terminal illness
Compassionate Use Trials
“Expanded Access Trials”
- Provide partially tested, unapproved therapeutics to a small amount of patients who have no other realistic options for treatment. Usually this involves a disease for which no effective therapy exists, or a patient who has already exhausted all other available options without success. Health must be so declined that they do not qualify for other randomized clinical trials.
- Case-by-case approval from the FDA and pharma company
Nominal data
There is no inherent value in the number, is simply associated with a group or outcome
Eg: Group 1, blood type AB
Ordinal data
Sense of a higher number reflecting something greater, but the difference b/w 1-2 may be different than that of 3-4.
If the scale is big enough the differences between the values become less different and the scale becomes more continuous.
Continuous Data
*Most informative
Intensity or measurement increases in a linear fashion, indicative by the magnitude of the difference.
P-value
Relative statement of the probability of how different two sets of data are, based on chance.
*Usually accept p-value of under .05
Observer Bias
Bias of the experimenter, based on expected outcome or intended results.
*Fix is double-blind experiment
Instrument Bias
Instrument outcome varies by factor
Subject Bias
Bias of the test system. Usually observable in clinical trials, where patients that know/think they are receiving a drug will have fabricated effects.
*Placebo effect - opioid system
4 types of Variability
- Within group
- Between group
- Within Subject
- Between Subject
Goal of the Design
Minimize: between subjects, within subjects, and within group variability
Maximize: Between group variability (Effect Size)
*Determines probability
The less variability within groups and subjects, the easier it is to determine a statistical effect.
Sample
A proportion of a population chosen to reflect characteristics of the population as a whole.
Sampling error
Selection of a sample that is bias, or not representative of a population as a whole
Convenience Sampling
Occurs when one selects a sample based on their accessibility
EX: choosing college students for a university study, picking people within the vicinity of my office
Judgement Sampling
Occurs when subjects are chosen by an individual familiar with the characteristics of the population
-Choosing subjects because of a pre-determined expectation of characteristics
Random Sample
Each subject within a population has an equal and uncontrolled chance at being included in the sample
- Clearly the least bias and least subject to sampling errors
- Done by chance - random generation, card pick method, number sample
Simple Random Sample
Type of random sampling in which all have equal chance - generally generated from a computerized list or random lottery.
Systematic Random Sample
Created by selecting one subject randomly and then choosing the remaining subjects at regularly spaced, randomized intervals, until the desired number of samples are reached.
Ex: Choosing the 28th person on a list, and then choosing every 25th person thereafter until 15 people are chosen.
Stratified Sample
Grouping of subjects into some type of logical characteristics. Ex: grouping high school students by class: Freshmen, Sophomores, Juniors, and Seniors. Then choosing 20 students from each class rank randomly = Stratified Random Sample
Cluster Sampling
Variation on the Stratified sample, in which characteristics of grouping may not be so obvious and can be arbitrary.
Ex: Randomly dividing high school into 4 groups, not based on class/age or any other variable, and then randomly choosing 20 students from those clusters.
Choosing 10 Random school districts in Illinois and then surveying every freshman in those 10 districts.
Purposeful Sampling
Occurs when subjects/cases are chosen because they exhibit particularly rich characteristics that will help in identifying results.
EX: Testing new Schizophrenia drug, and sampling only patients who exhibit ALL the DSM IV characteristics of Schizophrenia and excluding those who only show some characteristics
Falsifiability
Concept used to distinguish science from nonscience/pseudoscience. A result can be disproved, means it has the possibility of being scientific.
Merton’s norms of true science
Originality, Detachment, Universality, Skepticism, and Public accessibility
Accuracy
The degree of conformity of a measured or calculated quantity to its actual (true) value.
Precision
Also called reproducibility or repeatability, the degree to which further measurements or calculations show the same or similar results.
Standard Deviation
Characterization of precision
- 3% confidence interval of the measurements
* This means that 68.3% of the data collected will fall within one SD of the mean of the normally distributed data set.
Standard Error or Standard error of the mean (SEM)
is the estimated standard deviation of the error in method. It estimates the standard deviation between the measured values and the true value
*Always smaller than the SD
Variability of the means taken from several identical experiments
Repeatability
The variation arising when all efforts are made to keep conditions constant by using the same instrument and operator and repeating during a short time period.
Reproducibility
The variation arising from the same measurement process among different instruments and operators over a longer time period.
AKA: Robustness
Referring to a measuring device of machine = “robustness”
Refers to individuals who are scoring the same observations
Inter-rater reliability correlation
Determines the reproducibility of observers
Validity
Refers to the concept that a model is doing what you think it is modeling or measuring
*Refers to the concept, notion, design, or hypothesis
Internal Validity
The degree to which the intervention being evaluated really caused the effects estimated in the study
*Cause must precede the effect or change in IV must precede change in DV – if not, the change in DV is due to something else than the IV.
Temporal Precedence
The cause must precede the effect in time. –> IV changes before the DV
Covariation
The cause and effect are related in some way
* Change in IV = a proportional change in DV
EX: Change in the dose of Crestor = lower cholesterol
Nonspuriousness
There is no plausible or known alternative explanations for the observed covariation. Spurious means false, not authentic or genuine
Most difficult to rule out!
Threats to Internal Validity
Confounding Repeated Measures Biasing Subject Selection Bias Age/Maturation Effect Regression Towards the Mean Floor/Ceiling Effects Diffusion Effect Differential Drop-outs/Catastrophic Event
Confounding
A control flaw, where a variable other than the IV participates in a change in the DV. Can be a known variable, or one that is unknown.
*Considered spurious
Repeated Measures Biasing
Where prior exposure to the IV affects the outcome of the DV.
“Practice effect”, “carry over effect”, or “history effect”
Practice Effect (Carry over OR History Effect)
The experimental subject “learns” from the first assessment and this influences the outcome of the DV.
Subject Selection Bias
Unknown attributes of the subjects contribute to the outcome of the effects observed. Using a single characteristic to assign subjects to groups allows for ignorance of other characteristics that may effect the study outcome.
*Can be avoided by the use of pre-tests to reduce within groups variability. Also, non-biased, totally random assignments to groups overcome this as well.
Age/Maturation Effect
Effects that occur in long term studies, or those that include subjects being studied during a developmentally critical period.
Regression Towards the Mean
Outliers tend to regress towards the mean during subsequent assessments. This would assume that the extremes in the DV measurements may reflect some spurious effect during the assessment. A rat is feeling sick, or a human is having a “good day”. This can be accounted for by multiple pre-testing paradigms, however this can attribute to practice effects.
Floor/Ceiling Effects
When the DV can not decrease or increase any further– the degree of covariance erodes as the floor and ceiling are approached.
Diffusion Effect
Effects of the IV on the DV spread across groups. EX: Actions/behavior of a treated subject group may influence the behavior of the control group.
Differential Dropouts/Catastrophic Events
disrupt casual inference. *Common in long-term studies.
People being exposed to a new drug in clinical trial are dropping out much more frequently than those in the control group, due to side effects. This may tell you something about the IV!
External Validity
Refers to the ability of your experiment to be generalized outside of the experimental setting. Does my experiment apply to the real world?
PEOPLE - PLACES - TIME
Parts of External Validity
Face Validity Content Validity Construct Validity Predictive Validity Concurrent Validity Convergent Validity Discriminant Validity
Face Validity
The model looks like the system under study.
EX: Streptozotocin induced diabetic mice should have the same characteristics of a person with diabetes
Content Validity
The extent to which a measure represents all facets of a given target system or disease.
Should depict an overwhelming number of the characteristics of the target system/disease
Construct Validity
Model is representing what it is supposed to represent.
Ex: Administering an exam with political questions on it in an experimental design class (low construct validity)
Predictive Validity
Ability of a model to predict characteristics of the target under normal circumstances. ie: Treating an STZ model with insulin should prevent the symptoms of diabetes
Concurrent Validity
The ability to distinguish among the targets it should distinguish among if it were valid.
*Variation of content validity
A model of metastatic breast cancer should have cancer spreading to the lung and bone, but not the liver or development of leukemia
Convergent Validity
Idea that the model has characteristics similar to other models of the same target.
*Ie: There are many models of dementia, and your manipulation should work in all models.
Discriminant Validity
Related to convergent validity, but opposite, and suggests that a model should be different from models of other diseases.
Threats to External Validity
*Subjects, setting, and time* Population Validity Ecological Validity Temporal Validity Treatment-Attribute interactions Treatment-Setting interactions Multiple Treatment interactions Pre- and Post-test sensitizations
Population Validity
Does the model being studied apply to real-world situations
ie: does studying cancer in mice really reflect what’s going on in humans?
Ecological validity
Relates to setting, does one model setting apply to other model settings as well
ie: Does assessing learning methods in small suburban schools reflect the learning methods in inner city or rural schools?
Temporal Validity
Will the findings of the current model be applicable at all times.
Ex: Does purchasing patterns of teens in the 90’s reflect those of teens in 2010?
*More applicable to social research
Treatment-Attribute interactions
The fact that the subject’s response will depend upon certain attributes of the subjects and how those attributes interact with treatment
Treatment-Setting Interactions
Does the location a study is conducted in effect the outcome?
Ex: treatment of PD patients with Levadopa in a sterile clinical outcome to induce hallucinations as opposed to their normal home setting
Multiple-Treatment Interactions
Occur because of the effect of prior treatment influences the outcomes of the current study.
Ex: Usage of primates in multiple studies OR exclusion of patients due to other pre-existing medical conditions of medications
Pre- and Post-test sensitizations
Occur when subject’s responses or characteristics are altered by the testing paradigm.
Usually occurs when the intent of the study is realized by the participants, resulting in “Hawthorne Effect”
Hawthorne Effect
The characteristics, answers, or actions of a test subject change in correlation with the test paradigm.
*Once a test subject knows the reason or intent of a study, they may alter their behavior in favor of the predictable or “preferred” result.
Ie: workers being tested on productivity at different levels of area lighting were equally as efficient at very low/sub-optimal levels of lighting because they knew they were being observed for efficiency.
Reliability
Refers to the “repeatability” of an experiment. Refers to the idea that if you performed the same experiment multiple times, you would get the same results, repeatedly.
Inter-rater OR Inter-Observer Reliability
Used to assess the degree to which different raters/observers give consistent estimates of the same phenomenon.
*Two raters are trained in the same method and assess the same DV independently? Are their results highly correlated?
Test-Retest Reliability
Assesses the consistency of a measure from one time to another.
Parallel-Forms Reliability
Assesses the consistency of the results of two tests constructed in the same way from the same content domain
Internal Consistency Reliability
Assesses the consistency of results across items within a test.
Ex: exam in a class, did students who did well on one question, do well on other questions?
Bias
Can occur in the subject, observer, or instrument
*A prejudice in a general or specific sense, usually is a preference for one particular idea, person, or perspective.
Confirmation Bias
Acceptance or denial of the truth of a claim not based on the strength of arguments in support of the claim solely, but based on one’s own preconceived ideas
Systematic Bias
Bias resulting from a flaw integral to the system within which the bias arises
ie: A thermostat that consistently reads several degrees hotter or colder than the actual temperature
Preventing Bias
Blinding- single bind, double blind, placebo control, procedural control, sham control, random sampling
Automation - instrument certification
Certification of Observer
Repeated Measures
Refining the measure device
Reducing obtrusiveness of the measurement
Within Subject Variability
Will be small when your measurements are precise and reliable.
Can imply inherent variability within the subject
*Can be minimized with repeated measures testing. (can result in practice effects) –OR making multiple assessments of the same subject and then taking the mean of those measures.
Between Subject Variability
Implies that there is heterogeneity in the population (genetic variability)
*Can be a consequence of the IV
Can be large because there is inherent variability in the test subjects or because within subject variability is high.
*Can control for this with a matched-pairs design. –> placebo v.s test
Within groups Variability
measure of the variance for the measure of that group. The effect size can be large, but if the SD of the groups overlaps significantly, you will not see a significant effect.
- Can be consequence of within or between subject variance, or could simply reflect the variation in effect of the IV on the subject.
- Usually within groups variability contaminates studies the most.
Between Groups Variance
A reflection of the differences between two groups (Effect size) that we hope is a consequence of the IV. Assume two groups have similar within subject, within group, and between subjects variability, and as a result the effects of the IV spread between groups significantly (increased effect size). This increases confidence that the change between groups is due to the IV.
How to reduce Variability
Pre-test/pre-matching
Repeated Measures
Uniformity Trial
Pure random sampling
Pretesting/Pre-matching
Assessment of the DV prior to exposure to the IV.
Use this assessment to assign groups based on scores, can also do matched pairs. *Raises practice effects though
Uniformity Trial
a form of pre-testing designed to determine the variability of the environmental setting. *Addresses the environment-subject interaction
Experimental Unit
Identity of the thing being measured. *The minimal element to which the IV can be independently applied.
The physical entity which can be assigned at random to a treatment.
Sequence Control
The notion that certain patterns will emerge when you perform an experiment in the same sequence that can introduce bias or systematic bias.
*Overcome by running the subjects in a latin square!
Blocking
Another means of reducing variability. A way to group samples in subject groups
Randomized Block Design
Recognizing that there are inherent differences among your subjects and that they may contribute to variability. *Reducing in group variance.
Stratified Block Design
Variation on randomized block design in which there is inherent stratification within the blocks i.e: freshman, sophomore, junior, senior.
Matched Pairs Blocking
Experimental Units are assigned in pairs across levels of the IV. Can compare subjects with similar characteristics across the IV, with treatment or without, etc.
*Can block based on pre-matching scores, or known characteristics of the subjects, etc.
Powering the Study, Sample size calculation, or Power analysis
Determining the correct number of experimental units upfront.
Type 1 Error
“Error of the first kind” or Alpha error or “False Positive”
*The error of rejecting a null hypothesis when it actually is true. Accepting an alternative hypothesis (the real hypothesis of interest) when the results can be attributed to chance.
*Test claiming something is positive when it is actually negative
(Woman told she’s pregnant, but is not.
Type 2 Error
“Error of the second kind”, Beta Error, “False negative”
Accepting a null hypothesis when the alternative hypothesis is the true nature. Error is failing to observe a different when there actually is one.
(Woman is told she’s not pregnant, when she actually is.
Level of Significance
(Type 1/2 errors) determination of the probability for an error to occur
Bonferroni Correction
Correcting the probability of a type 1 error based on the number of comparisons required by a test.
One-tailed test
Assuming the IV will move the DV in one direction
Two-tailed test
Confidence that the IV will move the DV in one direction or the other, but not sure if it will increase or decrease.
Drop-outs
Loss of test subjects throughout the duration of the study.
- Animal deaths, patients lost to follow up, data is lost or somehow compromised, outliers,
- Can produce significant bias
Sampling frame
All the possible experimental units you can choose from.
ie: all the rats in your lab, all the people in a phone book, all the people who come to your clinic…
Complete random sample
Occurs when each unit has an equal chance of getting picked as a test subject.
Factorial Designs
Employ one or more IVs (called factors) and often have several levels of the factor.
One-way design
Type of factorial design, is the simplest. = one factor with several levels i.e dose response curve
Orthogonal
“perpendicular”, the direction of one data set does not predict the direction of the other. In other words, if data sets are orthogonal, they are not correlated. –Mutually independent, non-redundant, non-overlapping, irrelevant
Non-orthogonal
Correlated, as you increase one, you see a response in the other.
*Co-variation (test for internal validity)
control
Component of an experimental design that is identical in every way to the other components of the study with the exception of the factor(s) being studied
Cross-Over design
“Two period-two treatment” Test which involves two groups being tested at two intervals, in interval 1, one group gets IV, in interval 2 the opposite group gets the IV.
Matched Samples design
Special case of repeated measures where two different groups are pre-matched to be as identical as possible (randomized block design)
*Introduces a bias - not randomly chosen, but matched
Nested design
The grouping of test subjects or test items based on their relation to one another. ie: you would group all fetuses of one mother together when testing for the effects of cocaine on prenatal development. Take the mean of tests from all fetuses because they are all nested under the same mother.
Carry-over effects
Treatment received in one period is effected by treatments received in previous periods.
“wash-out” time
Time in which the IV is completely eliminated from the test system in between testing periods.
*Usually used in drug studies in cross-over designs
Differential Carryover
Prior exposure to the IV affects the subject in second exposure one way, and a different way in another condition
Reversal studies
The reversal of the effect of an IV.
- One of the most important means of establishing a true cause and effect relationship between the IV and DV.
- Withdrawal study, Antagonizing effect, competition study
Withdrawal Study
Withdrawal of the IV to see if the DV returns to baseline
Antagonize Effect
Administration of a second treatment that reverses the effects of the IV.
Competition Study
Similar the the antagonizing study, but in this case, the second IV administered competes with the first IV.
Epiphenomena
When other causes other than the IV can have similar effects on the DV. An unknown factor, possibly associated with the manipulation, is resulting in the observed effect.
Discovery Research
Type of research where there is a preconceived notion or general hypothesis, but not a specific hypothesis.
“Characterization Study” - where you assume the effect may emerge but you don’t know what that effect will be.
*Often a prelude to traditional research designs and generates future hypotheses.
Microarray Studies
Studies of alterations in genes
Proteomic Studies
Studies of alterations in proteins
Metabolomic Studies
Studies of alterations in metabolites
Bioinformatics
The use of computers to handle biological information
Ex: arrays, images, patient data sets, chemical structure etc
Data mining
Finding patterns between large groups of data
Translational Research
The ability to translate basic science discoveries into clinical applications, and to use clinical observations to generate research foci for basic science.
Bench to bedside “T1” research
Community to bedside to bench
3 elements of translational research
1) disease-based programs
2) Access to animal models and proximity to relevant patient groups
3) Ease of communication between basic scientists and clinicians
Model systems
Refers to animal models, culture models, computer-based models, or any other type of model that is used to conveniently reflect an element of nature or diseased state in a patient
Biological model
a manipulatable, adaptive representation of a biosystem that predicts and imitates the biological function of interest
*Does the model pathway differ from that in real life?
Disease model
A simulated representation of a condition of interest that imitates and predicts the characteristics of that condition while sharing a similar pathophysiology.
Preclinical testing
Testing of a drug that will later be used in the clinic and requires testing in animal models.
Subacute toxicity
Includes 3 or more routes of administration, at least 3 dose levels, 2+ species in small groups, Animal data used to predict human dosage, note effects on liver, kidneys, and how drug is cleared.
Chronic toxicity
3-24 months, tests for carcinogenic effects, teratogenic effects (malformation of fetuses) given to pregnant females.
Phase 1 clinical trial
Testing of the new drug in healthy volunteers (20-80) participants. Evaluates safe dose range, side effects
*3 types: SAD, MAD, and Food Effect trials
SAD (Single Ascending Dose) study
Small group of subjects are given a single dose of the drug, observed and tested for a period of time. If no adverse side effects are observed, the dose is escalated in a new group of subjects. Continues until the pharmacokinetic safety levels are reached, or intolerable side effects are observed (MTD)
Maximum tolerated Dose (MTD)
The dose at which intolerable side effects begin to manifest.
Multiple Ascending Dose (MAD)
Used to better understand the pharmacokinetics and pharmacodynamics of multiple doses of the drug. multiple low doses of the drug are administered and the patient is observed while blood samples and other fluid samples are obtained and analyzed to determine how drug is handled and eliminated by the body. Dose is escalated for subsequent subjects to predetermined level. “Feed and Bleed” study
Food Effect
Short trial used to investigate any differences in absorption of the drug caused by eating before the drug is administered.
*Usually run as a crossover study, where identical doses are given to two volunteers, one fasting, one after eating.
Phase 2 clinical trial
Drug is given to patients who actually have the disease (100-300) To test efficacy.
Phase 2A
Specifically designed to assess dosing requirements
Phase 2B
Specifically designed to study efficacy - how well the drug works at prescribed doses.
Phase 3 clinical trial
Drug is given to a large group of patients (1000-3000) to confirm its effectiveness and monitor side effects, drug is also compared to commonly used treatments
*Often multi-centered
Institutional Review Board (IRB)
committee of physicians, statisticians, researchers, community advocates, and others that ensure that a clinical trial is ethical and that the rights of the study participants are protected.
*Looks at internal validity
Inclusion/exclusion criteria
Medical or social standards that determine whether a person may or may not be allowed to enter a clinical trial. *factors such as, age, gender, type and stage of disease, previous treatment history, other medical conditions, etc.
Informed Consent
The process of learning the key facts about a clinical trial before deciding whether or not to participate. Must also continually inform patients throughout a study. *Must be in participants native language.
Adverse Reaction (Adverse Event)
Any unwarranted effect caused by the administration of drugs. Onset may be sudden or develop over time *All AEs must be reported to the IRB
Arm
Any of the treatment groups in a randomized trial.
Baseline
Information gathered at the beginning of a study from which variations found in the study are measured against. *A known value or quantity with which the unknown is compared against
Compassionate Use
A method of providing experimental therapeutics prior to final FDA approval for use in humans. This is used for very sick individuals with no other treatment options. Case-by-case approval from the FDA
Confidentiality
Maintaining the confidentiality of trial participants, including their personal identity, and all personal medical information
HIPAA
Health Insurance Portability and Accountability Act
Deals with protecting health insurance of individuals who lose or change jobs, and also the standardization of healthcare-related information systems
Open-label trial
Clinical trial in which the doctors and patients know which drug or vaccine is being administered
*Opposite of a blind trial, often the type of study used for weight loss drugs, or miracle supplements!
Data Safety and Monitoring board (DSMB)
An independent committee, composed of community representatives and clinical research experts, that review data while a clinical trial is in progress– ensures participants are not exposed to undue risk,
-Have power to stop studies
Standard of treatment
Treatment currently in wide use, approved by the FDA, considered to be effective in the treatment of a certain disease. Often what a new drug is compared to.
Study Coordinator
Members of a research team that are responsible for such things as recruiting, screening, and enrolling study participants, as well as ensuring adherence to GCP guidelines
Biological Model
A manipulatable, adaptive representation of a biosystem that predicts and imitates the biological function of interest
Disease model
A simulated representation of a condition of interest that imitate and predicts the characteristics while sharing a similar pathophysiology.
Operationalism
A fundamental concept which refers to the identification of measurable constructs that can be measured and in turn reflect a biological system or disease.
*Development of a model system is operationalizing the assessment of the disease of interest through a series of measures that are reliable and valid
Operational Definition
A procedure whereby a concept is defined solely in terms of the operations used to produce and measure it
In silico model
Computer simulations that are used to predict effects of an IV.
- Easy to set, but required enormous amounts of prior knowledge and data about the target system of study
- Implemented at a low cost.
- Study “what if” scenarios, how the manipulation of one variable changes or effects the other variables or system as a whole.
In vitro
Assessment of properties of the target system within a test tube or dish (culture plate)
*Involves tissues or cells dependent of the system they were derived.
Ex vivo
Assessment of relatively intact pieces of tissue or organ taken form an organism and then maintained in culture
*Studied immediately after removal from organism
In Vivo
Involved the assessment of the entire organism or animal
- improves external validity by decreases internal validity.
- studying an entire system comes with many more issues and higher complexity.
Predictive generalization
- The utility of a model is its ability to predict the target system under study. without predictive generalization (the ability of the model to accurately depict the target system) there is no reason to study the model.
- The more removed from the target system, the greater the difficulty for predictive generalization. This means less prediction for in silico, and more for in vivo
Predictive validation
The demonstration that a model predicts the target system
Cross validation
The act of testing prediction validation
*most common approach is to ascend the predictive generalization hierarchy
Ascend the predictive generalization hierarchy
Moving up models with greater assumed predictive generalization
Co-cultures
Cultures containing two sets of cells that normally interact with eachother
“Experiments of Nature”
Diseases or conditions that are the target of the model develop naturally
Ex: syncopic beagles
Model induction
Induction of the model by the experimenter.
*involves giving a chemical or inducing a lesion that mimics the condition you are trying to model.
Ex: STZ to induce T1D
*Two factors must be considered: The rate of induction, and the method of induction
Rate of induction
The rate at which the disease or condition of interest within the model system was produced by the experimenter.
*while natural induction is the best method, slower induction is considered better than fast induction because of the conservation of compensatory mechanisms and interactions with the rest of the body (more natural)
Compensatory systems
A change in one aspect of the system results in a change in other factors
*In slowly evolving disease, compensatory processes often induce dramatic changes in other system that may not have a chance to develop if the disease state is induced too quickly.
Method of Induction
Can include: physical techniques, toxins, drugs, chemicals, and genetic manipulation, in order to produce the disease of interest
Outcomes research
The collection and analysis of data gathered on the use of different healthcare products, procedures, services and programs, and the evaluation of the clinical, economical, quality of life, and patient satisfaction outcomes of that care to determine the value of those products, procedures, services and programs.
Comparative effectiveness research
Type of outcomes research designed to foster evidence-based medicine. Generally involves thousands of patients and seeks to determine which treatment is more effective.
Ex: Prevention trials, screening trials, diagnostic trials, treatment trials, quality of life trials, and Compassionate use trials
Prevention trials
Looks for better ways to prevent a disease in people who have never had the disease or to prevent a disease from returning.
May include medicines, vitamins, vaccines, minerals, or lifestyle changes
Screening trials
Tests the best way to detect certain diseases or health conditions
Diagnostic trials
Conducted to find better tests or procedures for diagnosing a particular disease or condition
Treatment trials
Test experimental treatments, new combinations of drugs, or new approaches to surgery or radiation therapy.
Quality of life trials
Explore ways to improve the comfort and quality of life for individuals with chronic or terminal illnesses
Compassionate use trials
(expanded access trials) provide partially tested, unapproved therapeutics to a small number of patients who have no other realistic options. Usually involve a disease in which no effective therapy exists, or a patient who has already exhausted all other options, and whose health is so poor they do not qualify for randomized clinical trials.
*Case-by-case approval must be granted by the FDA.
Complex behavior
An obscurely observable response of an organism to its environment.
Ex: anxiety, fear, depression, and parkinsonian
Encephalization quotient
Widely used measure of cognitive abilities between species.
*brain to mass ratio
Odds ratio
The ratio of the odds of an event occurring in one group, to the odds of it occurring in another group.
*Common association used in Case-control studies.
Meta-analysis
Combines the results of several studies that address a set of related research hypotheses
Taking data from multiple study outcomes and merging into one data sheet.
Relative Risk (RR) ratio
Ratio of the probability of contracting a disease following exposure to some factor, relative to the probability in the population not exposed.
