Research Final Flashcards

Question

What is the purpose of qualitative research?

Answer 1

* Development of theory * Study subjective experience, meaning and contextual aspects of human action and interaction * Exploration and discovery * Study individuals in their natural settings * Not interested in generalizability

Answer 2

Basis in anthropology, philosophy and sociology

Answer 3

* Multiple realities * Social reality is dynamic and contextual

Answer 4

* Exploratory not explanatory * Open not closed * Focus on meaning * How? What? Why?

Answer 5

1. Phenomenology 2. Ethnography 3. Grounded theory 4. Critical theory 5. Participatory action research

Answer 6

* Focus on lived experiences of a phenomenon * We can only understand a phenomenon through the experiences of those living with it/experiencing it * Researchers focus on understanding/describing the experiences of those living it * Interviews a common approach to data collection (but not the only one) - Do see focus groups - Don’t know in advance how many people you’ll need – can try to achieve data saturation (hard to do pragmatically and is done after the fact so hard to put in research proposal)

Answer 7

Inductive is from specific to general conclusions - see in phenomenology - specific experiences to general themes. Deductive is general premises to specific conclusion.

Answer 8

* Roots in anthropology * Description & interpretation of a cultural or social group or system * Fieldwork: prolonged observation of a group within a setting - Immersion – researcher being immersed - Fieldwork – prolonged observation in the natural setting (wherever that is – e.g., classroom). Prolonged is historically year or years. Observations can look different but are typically very detailed. - If you are researching and participating, you become so much part of the group that it might taint your understanding. Difference between observation and participant observation.

Answer 9

* Theory generation/construction as the focus * Researchers typically do NOT immerse themselves in published literature in advance * Common data collection: interviews, focus groups, observation Construct theory from qual data

Answer 10

* Focus on social realities that create barriers through dominant structures/processes. i.e., Challenging hegemony (dominant view of the world) * Common data collection: Discourse analysis of policy documents; case study; interviews; observation - About critique – understanding common understandings of issues, challenges and then putting it in the context of challenging some of those. Understanding political and social dominant structures that might be influencing our understanding of those.

Answer 11

* Engaging with those who are the focus of the research as research partners * Action and understanding are inextricably linked * Participatory approach from project formulation through to knowledge translation * Mixed methods of data collection are common -Assumes that the people who are meant to benefit from the research are active participants in the research from beginning to end. Design research question with you and are involved in every step. - PAR is in line with the idea of multiple truths and realities - Typically, the action is part of the research and you’re examining as a result of that action what changed, and you prepare a report based on that

Answer 12

Appropriateness & Adequacy * Appropriateness: select participants with exposure to the focus of the research * Adequacy: who can be engaged with a goal of saturation Often need to consider the pragmatics

Answer 13

Purposefully sought out ppl – e.g., ppl in first year of the program and aimed to get a range in terms of students ages, academic background and gender. Describe key characteristics as part of your samplings. Ask ppl what categories they fit in. Aren’t turning ppl away but are we getting a sample that ticks the important boxes in terms of your purpose. Intentionally picking someone based of a characteristic/criteria.

Answer 14

Research participants are asked to assist researchers in identifying other potential subjects.

Answer 15

Intent on trying to get as much variation from the group as you can – is a kind of purposive sampling

Answer 16

Used for sample size determination * Define – the sampling strategy (e.g., non-probability) * Explain – how you are implementing the strategy (e.g., purposive) * Justify – consider justification based on qualitative tradition, method of data collection, expected depth of data * Apply – consider pragmatic issues that might affect number of participants * Developed in response to critiques of “data saturation” as the determinant for sample size

Answer 17

Description and often interpretation

Answer 18

Small chunks of data that you can label in some way Generally, codes emerge from the data.

Answer 19

* Categories/Sub-themes o Once you have a set of codes identified, and perhaps a short description of each, consider how the codes link to each other? Can they be clustered together in some way that makes sense? * Themes o Can codes or categories be clustered together in a “bigger picture” idea or theme?

Answer 20

- Rigor/trustworthiness is the overarching theme of critical appraisal - Credibility - Transferability - Dependability - Confirmability

Answer 21

* Establishing believability * Strategies: o Prolonged engagement o Reflexivity o Member checking o Triangulation of data

Answer 22

Researcher immerses themselves as an observer or participant observer for prolonged amounts of time (ethnography) need a sense they were with participants long enough to believe them.

Answer 23

Critically examining your own beliefs and positionality – critical reflection – want a sense that they set themselves up for critical reflection. Did more than 1 person code/collect the data (more so triangulation) and have those people had critical discussion related to what they’re thinking/learning

Answer 24

Send the transcript back to the person you interviewed and ask them to review it to make sure it reflects what they were meant to say (can be controversial b/c they may want to change the data).

Answer 25

Collecting diff types of data, maybe from different types of people (e.g., profs and students).

Answer 26

* Can study findings be transferred to other contexts? * Strategies o Dense description of participants/sampling strategies - who was recruited and how o Findings described clearly and coherently with adequate supporting data to understand context and findings

Answer 27

* Consistency between data and findings - Do the quotes illustrate the points that they’re trying to make in the description of the findings * Procedural rigour * Strategies: o Audit trails o Detailed description of methods - Want a sense of how they did the coding, who was involved, did they have training, how often did they meet, how many ppl were involved. o Multiple researchers conducting analyses o Triangulation of analyses (not super common)

Answer 28

Record of all the transition/decision points you make once you have the data and are trying to interpret it.

Answer 29

* Analytic rigour/reducing bias in managing data * Strategies: o Rich description of findings (quotes support themes) - do they share quotes that support the themes/categories and do those quotes speak to how they describe o Audit trail re analysis o Reflexive analyses - have they talked about in the methods section they went through this sort of process o External audit - doesn’t have to be someone not on the research team – but maybe haven’t been involved in the coding part. That person might ask can I see how you developed these themes from this data Confirmability questions how the study findings are supported by the data. It identifies any bias that may have been present. It’s the level to which the findings can be confirmed or corroborated. Confirmability is concerned with determining that data & interpretations of the findings are not made up by the researcher’s imagination, but clearly derived from the data.

Answer 30

- Transferability is what we use in qual and generalizability we use in quant. Both talk about applicability. How can I apply this research to my setting/practice. Transferability has a real focus on the findings and the context. can I apply this to my situation? Can we transfer the findings to a different context? - Generalizing from the sample in the quant study are they generalizing to the sample I am working with. What are the characteristics of that sample?

Answer 31

Research question Design Methods Rigour

Answer 32

Treatment/Therapy - Does this intervention work? With whom? How well? For how long? Diagnosis - Will this measurement help me understand the condition? Prognosis - What is the likely outcome for this person/group of people? Etiology/Harm - How does this intervention/exposure affect the development of the condition?

Answer 33

Descriptive - how many? what factors? Relational - Degree and/or direction of association? Causation?

Answer 34

- Investigated as a potential agent of change in the dependent variable. - Intervention/exposure - Manipulated

Answer 35

- Thought to vary based on exposure to the independent variable - Outcome of interest - Measured NOT manipulated

Answer 36

- Not investigated but could influence the dependent variable - Covariate - characteristic separate from the IV that isn't of direct interest to the researcher but sometimes it might be controlled for (balance the groups based on it) or can use statistics - Confounder - can influence IV and DV so the results of the experiment don't represent the true relationship between the 2.

Answer 37

Yes = experimental study Did investigators randomly assign participants to receipt of the IV? Yes = RCT No = Non-randomized control trial (quasi-experimental study)

Answer 38

No = observational study Do investigators compare participants on presence of the IV? No = descriptive study Yes = Analytical study Do investigators look forwards or backwards in time from the intervention/exposure? Leads to cohort, case-control study or cross-sectional study.

Answer 39

Investigators decide who receives the intervention/exposure.

Answer 40

Each participant has the SAME chance of allocation to intervention/exposure

Answer 41

Aka quasi-experimental study. Each participant allocated to intervention/exposure based on non-random factors. E.g., Might have different sites where we recruit participants from and different sites might be allocated different levels of the IV.

Answer 42

Investigators do not decide who receives the intervention/exposure. More of a natural presence - it's there naturally in certain people.

Answer 43

Demonstrates possible association between the intervention/exposure and the outcome in a single group. E.g., here are some heavy smokers and many have lung cancer Here are some highly active older adults and relatively few of them have falls. 1 group, 2 variables, hints at a relationship so is often a starting point for more research

Answer 44

Explores reasons for possible association between the intervention/exposure and the outcome. Do control who they select to be the comparison group - still manipulated but not assigned. Can match between groups to eliminate some of the confounders.

Answer 45

Participants who do/do not receive are analyzed prospectively Look at ppl who do or do not receive a treatment and if they develop certain types of outcomes.

Answer 46

Participants who do/do not receive are analyzed retrospectively. Outcome is the starting point and then you look backwards for exposure.

Answer 47

Participants who do/do not receive are analyzed at a single point in time. Looking for relationship between exposure and outcome.

Answer 48

Look at reliability/validity of certain tools

Answer 49

Looking at if an intervention is worth developing further

Answer 50

Both have independent variables Both have comparison/control groups Both have dependent variables

Answer 51

Experimental - Assigned - Determined randomly or non-randomly - Prospective Observational - Present/observed - Exist/selected - Prospective/retrospective/ simultaneous

Answer 52

A systematic error that can distort measurement and/or affect investigations and their results. Uncontrolled phenomenon in a study that could potentially invalidate the results. Consider: direction & magnitude of bias

Answer 53

Selection Bias

Answer 54

Performance bias

Answer 55

Detection bias or attrition bias

Answer 56

Reporting bias

Answer 57

Participants or groups in a study sample differ systematically from the population at baseline. - How are participants recruited? - Who is enrolled in the study? - How are participants allocated to groups? - How is the allocation sequence concealed?

Answer 58

Inadvertent systematic differences between groups in intervention/exposure to other salient factors. - Are participants blinded? - Are interventionists blinded? - How are interventionists trained? - Is treatment fidelity assessed? Might be an inadvertent systematic difference between the amount of attention one group gets compared to the other - then maybe it's just the interaction impacting the DV.

Answer 59

Can we track the consistency of treatment between participants of 1 intervention. The extent to which delivery of an intervention adheres to the protocol or program model originally developed.

Answer 60

Systematic differences between groups in how outcomes are measured. - Are outcome measures objective/subjective? - Are outcome assessors blinded? A type of selection bias that results when one population is more likely to have the disease or condition detected than another because of increased testing, screening or surveillance in general.

Answer 61

Systematic differences between groups in withdrawals - Are outcome data for all participants reported? - Are reasons for attrition examined? Is there a trend that maybe the intervention is so hard to take that ppl can't handle it. Is outcome data for all reported? Have they told you what happened with the missing data? Was it analyzed? A type of selection bias due to systematic differences between study groups in the number and the way participants are lost from a study.

Answer 62

Systematic differences in reported vs unreported findings. - Are all identified outcomes reported? - Are statistically significant and non-significant effects reported and linked to analyses?

Answer 63

Randomly choose participants for the study. Important for generalization. Choosing participants for the study randomly from the population of interest. Helpful if you want to apply it to larger group.

Answer 64

Randomly choose group/receipt of the IV. Important to detect true effects of intervention on outcome. Only happens in experimental studies.

Answer 65

Which treatment people get. Random allocation is what they talk about when talking about RCTs. Often random sampling isn't possible in health research.

Answer 66

Categorical - Data has a discrete value in a distinct group. E.g., female and male or eye colour Continuous - Data can have any value in a defined range. Something that can go onto more of a number line.

Answer 67

Nominal - Categories are not ordered in a numerical way (e.g., hair colour) Ordinal - Categories have a natural numerical order but distance between categories is unknown (e.g., likert scale)

Answer 68

Interval - Values are equally spaced on a scale with no true zero (Celsius, IQ) Ratio - Values are equally spaced on a scale with a true zero (grip strength)

Answer 69

How well does a measure capture what it intends to measure?

Answer 70

Can results from a measure be reproduced under the same conditions? If I administer a test at diff times of day or someone else administering it do you get the same results?

Answer 71

To what degree does a measure capture change?

Answer 72

How useful is a measure for informing practice for different types of clients? Are measures culturally useful and appropriate

Answer 73

Statistics allow us to use the sample to make, justify and qualify inferences about the population. Also allow us to identify when patterns in the sample are likely due to real relationships/differences between variables.

Answer 74

Study design Study execution Study results

Answer 75

Understanding research evidence Evaluating research evidence Applying research evidence

Answer 76

Use the sample data to make inferences about the population. Using the subset to learn about the whole. - Prove or disprove a theory/hypothesis - Determine relationships or association between variables.

Answer 77

Summarize the main features of the sample data. Describe the state of the independent, dependent & extraneous variable(s) in the sample and/or sample groups at particular time points in a study. Helps you understand who the participants are.

Answer 78

n = frequency count % = proportion Frequency = total # of occurrences

Answer 79

RF = total # of occurrences/total # of possible occurrences Get a decimal which you can then multiply into a percent if needed. Variable levels are MUTUALLY EXCLUSIVE

Answer 80

Used for frequency

Answer 81

Categorical labels on x axis Numerical labels on y axis Bars typically separated by space Bar charts are for categorical data!

Answer 82

In continuous data the bins need to be the same size with no gaps in between. Data is binned into discrete categories. bins are mutually exclusive. Total frequency = total # of participants bins are of equal numerical size with no gaps in between. E.g., age might have categories of 40-44, 45-49, 50-54, 55-59 etc.

Answer 83

Used to summarize continuous data (frequency distribution) Numerical label on x axis Numerical label on y axis Bars typically not separated by space

Answer 84

Median Median is best b/c an assumption is made when calculating mean that it's continuous and space between points is equal. And that's not the case.

Answer 85

Not often used with continuous data, but is useful in summarizing categorical data.

Answer 86

Skew the frequency distribution

Answer 87

Most precise Most sensitive to change Point estimate for population mean in a normal distribution Sample mean in normal distribution is the best option of what the mean would look like in the population.

Answer 88

Tail is to the left (negative side). Mode is highest peak but mean is more to the left than median b/c mean gets pulled.

Answer 89

Tail is to the right (positive side). Mode is highest peak but mean is more to the right than median b/c mean gets pulled.

Answer 90

Measure of dispersion Length of the interval that contains all the data. Range = highest data point - lowest data point - simple to calculate - misleading when there are outliers or when data sets are very small

Answer 91

Summarizes data set by describing how widely spread out it is.

Answer 92

Measure of dispersion Range of the middle 50% of data set sorted by ascending numerical order. = interval from 25th percentile to 75th percentile. order data set, find median, find centre of upper and lower halves of data set. More robust to outliers and skewness than range Shown usually as IQR = Q1-Q3 (not a minus just the range). if shown as Q3-Q1 will see just one value.

Answer 93

Measure of dispersion Box covers middle 50%. Edges are at Q1 and Q3. length of the box is IQR. The dotted lines (whiskers), extend out from the box to indicate how far the data extends out past that IQR. Don't typically expand further than 1.5 x IQR then beyond that is an outlier. In the box is a line representing the median

Answer 94

Measure of dispersion Average of the squared difference of each data point from the sample mean. Variance = Sum of differences between the data points and sample mean, squared divided by total # of data points SUM the squares Squaring makes the differences positive to avoid canceling Final number isn't meaningful to us. We use it to get to SD.

Answer 95

Measure of dispersion Average of the absolute differences of each data point from the sample mean. Standard deviation = square root of variance - Most robust and accurate measure of dispersion because it uses all the data points - Expressed in the same units as the data

Answer 96

approx 68% fall within 1 SD of the population mean approx 95% fall within 2 SD of the population mean approx 99% fall within 3 SD of the population mean

Answer 97

= number of population standard deviations away from population mean. useful as a standard score that applies across variables.

Answer 98

Frequency and proportion

Answer 99

Frequency Measures of central tendency Measures of dispersion

Answer 100

Is typically very specific and usually resolved through a closed-ended search process. o E.g., an OT wanting to know the prevalence, etiology, prognosis and functional implications of a disease o The information retrieval task is to identify an appropriate info source and to access the info

Answer 101

An iterative and ongoing information-seeking process that involves successive steps to arrive at info that is as close as possible match to the info being sought.

Answer 102

Words or phrases that re entered into the interface of online information-retrieval tools.

Answer 103

Journal in which submitted articles are rigorously evaluated by members of an editorial board who have expertise in research methods and in the topic area under study Articles are published research studies, review articles, and other commentaries that have met with sufficient approval from the members of the editorial review board of a journal to be included in the journal publication.

Answer 104

o Structured browsing involves a preplanned organization of a list of topics. This approach follows a directed path to the information sought o Serendipitous browsing is a more random process. Nonlinear path of info.

Answer 105

Involves seeking matches to a particular text or keyword

Answer 106

1. What (am I looking for)? 2. Where (can I find it)? 3. How (do I access and retrieve it)? 4. How well (does it satisfy my info requirements)?

Answer 107

Refers to info that is not published or available in usual formats such as journals. E.g., abstracts of conference papers, dissertation or unpublished thesis reports.

Answer 108

To discover cause and effect relationships by comparing 2 or more individuals or groups based on differing outcomes associated with exposure or interventions.

Answer 109

Bottom to top: Animal and lab studies Case series and case reports Case control studies Cohort studies RCT's Systematic reviews Meta-analysis

Answer 110

A statistical technique that summarizes the results of several studies in a single weighted estimate, in which more weight is given to results of studies with more events and sometimes to studies of higher quality

Answer 111

A review in which specified and appropriate methods have been used to identify, appraise, and summaries studies addressing a defined question. (It can, but need not, involve meta-analysis). In clinical Evidence, the term systematic review refers to a systematic review of RCTs unless specified otherwise

Answer 112

A trial in which participants are assigned to 2 or more different treatment groups. In Clinical Evidence, we use the term to refer to controlled trials in which treatment is assigned by a method other than random allocation. When the method of allocation is by random selection, the study is referred to as a RCT. Non-randomized controlled trials are more likely to suffer from bias than RCTs.

Answer 113

Prospective

Answer 114

A study design that examines a group of people who have experienced an event (usually an adverse event) and a group of people who have not experienced the same event, and looks at how exposure to suspect (usually noxious) agents differed between the 2 groups. This type of study design is most useful for trying to ascertain the cause of rare events, such as rare cancers.

Answer 115

Analysis of series of people with the disease (there is no comparison group in case series).

Answer 116

When investigators make use of existing concepts and knowledge, including wisdom received from others while growing up as human beings and from professional training.

Answer 117

Investigators keep their eyes open to see new ways and build up new ideas

Answer 118

Individual is not conceptualized as a willful, autonomous person. Individuals are viewed as bound by social rules or norms; they are defined simply as the sum of family, work and community roles.

Answer 119

1. The lived space (spatiality) 2. The lived body (corporeal embodied experiences) 3. Lived social relationships (relationality) 4. Lived time (temporality)

Answer 120

1. Participation in the setting 2. Direct observation 3. In-depth interviewing 4. Analyzing written documents and material objects

Answer 121

Hawthorne effect Threatens validity

Answer 122

* In one form, “elite” interviews are conducted with individuals to be considered to be influential, prominent, and/or well-informed people in an organization or community. * Key informants (elites) are specifically selected for interview on the basis of their expertise in areas relevant to the research

Answer 123

* When multiple methods of data collection are used in the same study, this is called triangulation * This is one way of increasing the rigor of qualitative study * Refers to the use of 2 or more strategies to collect and/or interpret or analyze information * Purpose is to validate a particular finding When triangulation between observers is done might see peer debriefing

Answer 124

Project-based methods include daily operational procedures that help to minimize errors in all processes related to data collection, data storage, and data management.

Answer 125

Serves as a means of reliability checking for both the procedures and conclusions of a study

Answer 126

Qualitative analysis is about understanding meanings, process, people, and their thoughts and actions through the interpretation of people’s words

Answer 127

Inscribing social disclosure is a deliberate act to ensure that interactional details (e.g., in a semi-structured interview) are fully captured

Answer 128

1. Perform a formal analysis or interpretation of one data source. 2. Select a particular code for further analysis 3. Compare and contrast data sources using a particular code (same code from step 2) 4. Draw some general conclusions about what a coding strategy or arising data pattern means.

Answer 129

This is the systematic approach and techniques used to ensure reliability and validity of the study.

Answer 130

Trustworthiness is concerned with how the researchers establish the study findings as credible, transferable and confirmable.

Answer 131

* Two-group post-test only randomized experiment is the most basic experimental design in which participants are randomly assigned to either a treatment group or the no-treatment control group o Both groups are assessed following the treatment to see if they differ on the desired outcome. o There is no pretest assessment in this design b/c the random assignment to groups renders the groups probabilistically equivalent (i.e., although the 2 groups are not equal in terms of all variables, any differences between the 2 groups are likely based on chance rather than on some systematic pattern of variation).

Answer 132

* The two-group pretest-post-test randomized experiment is nearly identical to the other method, but there is the addition of a pretest before the treatment is offered o Addition of a pretest introduces greater control within the experiment in that it allows for the measurement of change within the 2 groups of participants o Further demonstrates that any observed difference between groups did not occur independently without the treatment and was not attributable to error, such as unanticipated difference between participants in the 2 conditions.

Answer 133

1. Placebo - led to believe they are receiving a treatment of significant benefit 2. Usual-care - continue to receive what is considered the usual standard of care for that impairment. 3. Delayed-treatment - receive the treatment after a period of time after the treatment group has already received it. 4. No-treatment - participants are naive to any treatment for their impairment or have independently withdrawn from or have deliberately been withdrawn from treatment for purposes of the study

Answer 134

Often utilized in quasi-experimental designs, in which control groups still exist , but participants are not randomly assigned to a condition and so are more likely to be aware that they are not receiving the experimental treatment.

Answer 135

* Quasi-experimental designs utilize random selection or other methods of non-random assignment to groups based on convenience sampling, in which participants may be fully aware of the group to which they are being assigned, and researchers estimate that groups are equivalent in terms of key features, but they cannot be as sure as if the groups were determined by random assignment. * Quasi-experimental designs allow for ethical concerns about feasibility of implementation to be addressed

Answer 136

* Include studies that are purely descriptive or observational in which variables that are thought to be associated with one another are analyzed statistically o Aka correlational b/c the central question concerns an association between variables that may not be causal or ordered in a specific way * Typically lacks manipulation of an independent variable and only relies on measurement of information

Answer 137

A study is said to have fidelity if there is documentation that the IV is administered just as planned.

Answer 138

A participant assigned to one condition actually experiences some or all the comparison condition

Answer 139

(aka sensitivity) is the degree to which a dependent variable shows appropriately small but meaningful increments of change over time. o A 3-point scale might not show progress to show on the measure

Answer 140

* A ceiling effect occurs where the sample’s scores are already so high on the scale that little improvement is possible. o A floor effect occurs when the opposite is the case

Answer 141

Does not predict which version of the IV is better, just that one is better (superior).

Answer 142

Nominal - 2 or more categories Dichotomous is 2

Answer 143

The extent to which an observed difference (or improvement) occurs by chance is referred to as sampling error

Answer 144

In stats, the probability of a true difference or improvement is represented as a p value. The p value is used as a cutoff point to determine the extent to which a conclusion about a sample reflects a true difference within the larger population, versus the conclusion being due to error or chance P-value is the probability that the results you have could have happened by chance.

Answer 145

The process by which outcomes or significant differences found in a study reflect true outcome or are due to chance or error. Is there enough strength of evidence to be able to reject the conclusion that the observed outcomes/differences are due to error/chance.

Answer 146

States that an observed difference or outcome is due to chance. Point is to reject the null.

Answer 147

Specifies a relationship between variables that is not due to chance. Relationship may be directional or nondirectional.

Answer 148

Parametric statistics is a branch of stats that assumes that sample data come from a population that follows a probability distribution based on a fixed set of parameters. * Parametric statistical tests may be used provided that the following criteria are met: o The dependent variable(s) being measured are continuous (i.e., use an interval or ratio scale); and o The sample size is large enough (N>30) so that assumptions about normality and variance are likely to be met

Answer 149

When a statistical test is being performed on variables from the same sample group, it’s referred to as a related-samples test.

Answer 150

When a statistical test is being performed on variables from 2 or more different sample groups, it’s classified as an independent-samples test. AKA between-subjects test

Answer 151

* A positive relationship means that the 2 variables increase or decrease in tandem. * A perfect negative relationship means that as one variable increases, the other decreases

Answer 152

o R = 0 to +/- 0.20 suggests a negligible relationship between the two variables o R = +/ 0.20 to +/- 0.40 suggests a low correlation o R = +/- 0.40 to +/- 0.60 suggests a moderate correlation o R = +/- 0.60 to +/- 0.80 suggests a high correlation o R = +/- 0.80 to +/- 1.00 suggests a very strong relationship

Answer 153

Independent-samples t-tests compare the means from 2 independent groups or samples

Answer 154

* Paired-samples t-tests compare the means from a single group of clients, typically at 2 points in time * Also denoted as a t Can be the same individual but at 2 points in time

Answer 155

A one-way analysis of variance (ANOVA) allows you to test differences between 3 or more means (or levels) of a single independent variable. * In a one-way ANOVA, scores for each level of the independent variable on some anticipated outcome are reflected on values for the dependent variable * The term one-way refers to the fact that this test allows you to only test a single independent variable. * The statistic that denotes whether the means from different levels are equal or different is denoted as F.

Answer 156

* Nonparametric statistics and statistical tests are used when assumptions about normality and homogeneity of variance are not met. * Generally this is the case when: o The dependent variable(s) is nominal or ordinal and o The sample size is small (N<30)

Answer 157

An x% confidence interval is interpreted as indicating a range within we can be x% certain that the true effect lies. Larger studies tend to give more precise estimates of effects (hence have narrower Cis) than larger studies. With precision see narrower CIs.

Answer 158

Power is the ability of a study to demonstrate that there is a difference if one exists Determined by several factors: magnitude of observed differences (effect size), variance - power increases as variance with data is reduced and sample size (n). Need a large sample size to get greater power.

Answer 159

RQ: - Specific and explicit - Describe sample, design, intervention, how the outcome will be measured, over what period of time. Hypothesis: - State null hypothesis based on formulated research question.

Answer 160

A hypothesis predicts the direction of the relationship between 2+ variables of interest. Directional - predicts the path and direction of the relationship Nondirectional - predicts the path but not the direction. Null (statistical) - predicts there is no relationship between or among the variables under study We seek to disprove the null Path = association/relationship

Answer 161

1. State the hypothesis 2. Set the criteria for a decision 3. Specify and compute the statistic 4. Make a decision

Answer 162

Assume it's true unless we can prove otherwise

Answer 163

Level of significance Usually set at 5%, lower makes it harder to reject the null. This is chosen/stated before hand. This helps you determine sample size needed for study. If alpha criterion is set at 1% will probably need a larger sample. Most researchers set it at 5%. P value tells us if we've met that %. Can report the p value to show where your data actually lies so might set alpha a little higher, results can be better than that.

Answer 164

Test statistics allow us to determine how likely the sample outcome is at accepting (i.e., no difference) or rejecting (i.e., a difference exists and in what direction) the null It's the method used to give you a result and whether or not that result is significant or not. - Begin with dataset (sample) - Test data for (normal) distribution - Distribution --> statistical test --> test statistic - Reject the null if the value of the test statistic is less than the alpha criterion If normal run parametric tests

Answer 165

1. Fail to reject H0, fail to accept Ha - Done if insufficient evidence to reject the null 2. Reject H0, accept HA. - Done when there is sufficient evidence to reject the null

Answer 166

Reject H0 when H0 is true - We conclude that an intervention is of benefit when it's not

Answer 167

Fail to reject H0 when HA is true - We conclude that an intervention did not show benefit when it really does work - Could be a result of a small sample size

Answer 168

1 minus beta

Answer 169

1. Differences between groups - Intervention group mean is different than control group mean 2. Differences within a group 3. Association between variables

Answer 170

Non continuous data Like a t test but for nominal or ordinal data.

Answer 171

- Analysis of 2 means - Data are continuous - Data re normally distributed - 2 samples are independent

Answer 172

- Overall comparison between at least 3 independent sample (group) means - Inferences about means are made by examining the variance of the samples - Will tell you if there is a difference but won't tell you which groups are different from each other. Gives you more of a superficial level of info.

Answer 173

- Range of values from your sample that has a high probability of containing the true population value - Tells you precision and location - Length changes with changing SD and sample size - Typically the critical value to determine level of convince is 95%

Answer 174

Measures the degree of association between 2 continuous variables (including direction and strength). Can't predict one from another

Answer 175

Helps us describe the relationship between variables more accurately How is independent variable (x) associated with dependent variable (y) With regression you can make the predictive analysis. Dependent variable on one side of equation Independent + other variables on the other side of the equation Allows you to consider the association between multiple variables to understand their influence together on the dependent variable Regression for continuous dependent Logistic regression for nominal data (get an odds ratio out of it) Can use regression to predict things. Correlation only looks at 1 comparison, regression is multiple.

Answer 176

Outcome variable is dichotomous or categorical Put ppl in a category and determine an odds ratio for that. E.g., % of ppl employed or unemployed. Then you can try to determine factors associated with that

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Standardized mean difference and effect size are used interchangeably Looking at difference between experimental mean and control mean and normalized/standardized to the variant. P-value tells us a difference exists that didn't occur by chance; Effect size tells us more about how big the difference actually is. A way to standardize the way that we measure differences between groups in inferential statistics Effect size tells you how meaningful the relationship between variables or the difference between groups is. It indicates the practical significance of a research outcome. A large effect size means that a research finding has practical significance, while a small effect size indicates limited practical applications.

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0.2 = small 0.5 = medium 0.8 = large How large is the difference between means, taking into account the variance?

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Like the histogram, the X axis is in theory in the same unit as the variable but is not binned so that we have the nice smooth curve that you see here The Y axis captures Probability Density = likelihood of observing a value on the x axis in the population

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Probability of type 1 error (reject the null but the null is true - false positive)

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P values get smaller as sample gets bigger

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Comparing means

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Causation is controlled by study design, not statistics.

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Questions that focus on - How much and how - Quantity and meaning - Perceptions and change

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Mixed methods is quant and qual combined. Multimethod could be two different forms of quant or qual. Mixed method is intentional combination of qual or quant

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The tradition in CAPS is the one taking priority E.g. QUAL + quan is giving qualitative research priority Sequential design is indicated by --> First one is used to guide the second method. Concurrent design is indicated by + Transformative – implies the goal is to change something (not just understand) Generally, the typology is related to data collection.

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Nested – always concurrent. E.g., nested quantitative inside qualitative – one circle is inside the other, taking account of the quant data within a larger qual approach. Nested is about sampling – if you did a big RCT on something you might sample from within the sample a subgroup of ppl who experienced the intervention on how they experience it. Can still be sequential even though it’s nested.

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- Consider methodological integrity - Converting Data to allow integration Somewhere in the paper, they should be integrating the results across qual and quant.

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Mixed methods appraisal tool.

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1. Are there clear research questions? 2. Do the collected data allow to address the research question?

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CASP - Critical appraisal skills programme

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Used the Dartmouth in class - Patient follow-up - Randomization - Intention to treat analysis - Similar baseline characteristics of patients - Blinding - Equal treatment - Conflict of interest

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1. Recognize the theoretical drive of the project 2. Adhere to the methodological assumptions of the core 3. Recognize the role of the imported models to the project 4. Work with as few data sets as possible

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Discovery or testing

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In mixed methods Exploratory = primarily qualitative Explanatory = core method is quantitative

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Either one can be

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Larger studies provide more accurate estimates effects which means they are narrower.

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Helps us compare variation between measures with different units.

Research Final Flashcards

(223 cards)