Experimental Design Flashcards Preview

My cards > Experimental Design > Flashcards

Flashcards in Experimental Design Deck (201):

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


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.


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.
*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



*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.



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

1. Within group
2. Between group
3. Within Subject
4. 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.



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



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



The degree of conformity of a measured or calculated quantity to its actual (true) value.



Also called reproducibility or repeatability, the degree to which further measurements or calculations show the same or similar results.


Standard Deviation

Characterization of precision
68.3% 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



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.



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



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



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



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

Repeated Measures Biasing
Subject Selection Bias
Age/Maturation Effect
Regression Towards the Mean
Floor/Ceiling Effects
Diffusion Effect
Differential Drop-outs/Catastrophic Event



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?


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.



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?



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

Repeated Measures
Uniformity Trial
Pure random sampling



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!



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.



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



"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



Correlated, as you increase one, you see a response in the other.
*Co-variation (test for internal validity)



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.



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



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



Any of the treatment groups in a randomized trial.



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



Maintaining the confidentiality of trial participants, including their personal identity, and all personal medical information



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.



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



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.



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.