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Advantages of Content analysis

Looks directly at communication via texts or transcripts, and hence gets at the central aspect of social interaction. Can allow for both quantitative and qualitative methods Can provides valuable historical/cultural insights over time through analysis of texts Is an unobtrusive means of analyzing interactions Provides insight into complex models of human thought and language use

Retrospective Cohort Study

(Already happened). Data are already collected and a researcher simply records what is known or has been collected on a group or cohort. This takes less time since the data are already collected and may even be computerized for easy accessibility.

ANALYSIS OF VARIANCE FAMILIES (ANOVA, ANCOVA, MANOVA, MANCOVA)

ANOVA are: Eta-squared and partial eta-squared. Eta-squared and partial eta-squared are estimates of the degree of association for the sample. The software, SPSS for Windows, displays the partial eta-squared statistics when you check the display effect size option. Partial when more than 1 Independent Variable.

Nonprobability Sampling

A type of sampling that does not involve random selection

Single-Case Designs/Single Subject Should include FOUR features

1) Continuous assessment 2) Baseline assessment 3) Stability of performance 4) The use of different treatment phases

There are 6 types of data that can be collected in case studies! They are:

1) Documents 2) Archival records 3) Interviews 4) Direct observation (may include video) 5) Participant observation 6) Artifacts

Advantages of case studies

1) May provide an abundant/fertile source of information. 2) Possible to study a characteristic/attribute quite intensively 3) Can focus on rare, unique, and extreme cases (aka, small n study)

The Value of Case Studies

1) Source of ideas and hypotheses 2) Source for developing therapy techniques 3) Study of rare phenomena 4) Persuasive and motivational value - provide evidence for grants application that would fund a larger empirical study

Yin offers 5 basis components of a case study design:

1) The study's question (s) 2) The study's propositions (if any) 3) The study's units of analysis (es) 4) The logic linking of the data to the propositions 5) The criteria for interpreting the findings

Disadvantages of case studies

1) This method is not scientific - nonrandom sample, non-generalizable conclusions 2) Observer may be biased 3) Subject is usually aware that they are being studied 4) Many threats to internal validity may occur such as maturation, testing, history

Conducting meta-analyses

1)Location of studies 2)Quality assessment 3)Calculating effect sizes 4)Checking for publication bias

Exploratory case study approach

Actually try to show a cause and effect. A design in which the researcher first begins by exploring with qualitative data and analysis and then uses the findings in a second quantitative phase. Intent is to develop better measurements with specific samples of populations and to see if data from a few individuals (in qualitative phase) can be generalized to a large sample of a population (in quantitative phase). Example: researcher would first collect focus group data, analyze the results, develop an instrument based on the results and then administer it to a sample of a population.

Advantages of cohort studies

Allows a researcher to study something that would be unethical in a randomized control study. Since these studies allow the researcher to demonstrate that the cause(s) occurred before the event of interest, it enables him/her to determine "cause" instead of not knowing which is the cause and which is the effect Also, a single study can measure several variables that may be both risk factors or outcomes (e.g., depression, anxiety, PTSD)

Quota Sampling (similar to stratified sampling without random selection)

Basically you stratify your participants on some characteristic to mirror that of the general population or the study population of interest. Get number of participants to meet quota without randomize sampling.

Cohort Study (aka longitudinal study)

Best used to determine the incidence of a condition/disease/syndrome. Group of individuals that are followed over time. Data can be collected either prospectively or retrospectively

Cross-Sectional study

Best used to determine the prevalence of a condition, disease or syndrome. They may also be used to infer causation. This type of study assess participants at one point in time. Data is collected on whether an individual has been exposed to an event/condition/stressor/etc., and whether they have the outcome of interest (i.e., disease, syndrome, PD). Looking at people at one period of time.

Disadvantages of content analysis

Can be extremely time consuming Is subject to increased error, particularly when relational analysis is used to attain a higher level of interpretation Is often devoid of theoretical base, or attempts too liberally to draw meaningful inferences about the relationships and impacts implied in a study Tends too often to simply consist of word counts Often disregards the context that produced the text, as well as the state of things after the text is produced. Can be difficult to automate or computerize

Disadvantages of case-control studies

Can only look at one outcome/event/condition Bias is problem - Two types: Sampling bias - how were the participants with the condition sampled or obtained. Observation and recall bias - since data are collected retrospectively, there may be bias on the part of the subject and researcher to determine if predictor or risk variables occurred.

Disadvantages of cohort studies

Cohort studies are not as reliable as randomized controlled studies, since the two groups may differ in ways other than the variable under study. Other problems with cohort studies are that they require a large sample size, are inefficient for rare outcomes, and can take long periods of time if retrospective. (BIGGEST PROBLEM) Additionally, participant loss (i.e., attrition) is often a problem as time increases.

Types of Content Analysis

Conceptual Analysis (Main type) and Relational Analysis.

Use of content analysis

Content Analysis has been used as a method of research in marketing and media studies, to literature and rhetoris, ethnography and cultural studies, gender and age issues, sociology and political science, psychology and cognitive science and is beginning to be used in the legal field.

Content Analysis

Counting words/text! The concept of content analysis begin in the late 1930s. Although initially limited to studies that examined texts for the frequency of the occurrence of identified terms (word counts), by the mid-1950s researchers were already starting to consider the need for more sophisticated methods of analysis, focusing on concepts rather than simply words, and on semantic relationships rather than just presence.

Explanatory case study approach

Describing case and go further (environment, family situation etc). go outside the case. Overall intent is to have the qualitative data help explain in more detail the initial quantitative results. A typical procedure might involve collecting survey data in the first phase, analyzing the data, and then following up with qualitative interviews to help explain the survey responses.

Publication Bias

Editors want to make money so they want you to pay for their articles or subscribe to their journal. Editors don't want to publish the negative findings such as "Vitamin C does not prevent the common child!" This article will go to File 13!

Glass's Delta

Effect size measure may differ considerably from Cohen and Hedges since it is based on only one group (the control). Proposed an estimator of the effect size that uses only the standard deviation of the second group. The second group may be regarded as a control group, and Glass argued that if several treatments were compared to the control group it would be better to use just the standard deviation computed from the control group, so that effect sizes would not differ under equal means and different variances.

Conceptual Analysis

Establishes the existence and frequency of concepts most often represented by words of phrases in a text.

Three case study approaches

Explanatory, Exploratory, & Descriptive

Narrative Literature Review

Generally based on a subjective selection of publications through which the reviewer qualitatively addresses a question summarizing the findings of previous studies and drawing a conclusion. There can be author(s) bias since the review does not follow a clear methodology. The lack of a specific search strategy increases the risk of failing to identify relevant or key studies on a given topic thus allowing for questions to arise regarding the conclusions made by the authors. Narrative reviews should be considered more as opinion pieces than evidence-based.

Baseline assessment

Generally refers to the observation of an action/behavior for several days before an intervention is applied (also referred to as the baseline phase)

Case-Control study (Spray has most experience with)

Generally retrospective in that individuals with the condition are usually matched with a controls who does not have the condition. This type of study may determine the importance of a predictor variable in relation to the presence or absence of the condition of interest. Case-control studies are generally used to calculate the odds of someone developing the event or condition given they have, or have been exposed to, the predictor variable.

Convenience Sampling (aka, accidental)

Getting a sample of individuals that are convenient. Can't generalize findings to general population unless the study is specific to that one population. (Ex: go to the mall)

Relational Analysis

Goes one step further by examining the associations among concepts in a text.

A-B-A Design

If a change in behavior (or whatever you are measuring) occurred during B and is actually due to the treatment or intervention, then change should disappear when B is removed and the measurement of behavior should return to the baseline value. Conversely, if a change in B was due to some extraneous variable, then the change will not disappear when treatment/intervention is removed. Thus, the A-B-A design allows a causal relation to be drawn

Multiple-baseline design

In this design, the effects of an intervention are assessed across several participants, behaviors, and/or settings. May help to control for confounds by introducing treatment at different times for different participants, behavior, and/or settings. It s important that the baseline data are constant for second participant or behavior or setting before introducing the intervention/treatment. If they stay the same way, we know it is unlikely that something else is affecting it besides the intervention.

Prospective Cohort study (two groups)

In this study type, two groups (i.e., cohorts) are followed. One group has been exposed to a certain condition, etc., and the other group has not been exposed. The group that has not been exposed is known as an external control.

Prospective Cohort study (single group)

Individuals are selected who do not have the condition of interest (e.g., substance abuse). They are followed over a period of time and a variety of variables may be collected at baseline (so to speak) and at multiple time periods depending on the study. All individuals are observed to see who will develop the condition. Those individuals who do not develop the condition as considered as internal controls.

Meta-Analysis

Must contain a systematic review. The statistical analysis of a compilation of individual studies. Most often used to assess the clinical effectiveness of healthcare interventions; it does this by combining data from two or more randomized control trials. Trials provides a precise estimate of treatment effect, giving due weight to the size of the different studies included. The validity of the meta-analysis depends on the quality of the systematic review on which it is based. Good meta-analyses aim for complete coverage of all relevant studies, look for the presence of heterogeneity, and explore the robustness of the main findings using sensitivity analysis.

Observational Research Methods

Observational studies are often performed in clinical settings and seek to determine either prevalence, incidence, cause, or prognosis. They may be used to study (1) events that might be considered unethical to study in an experiment or quasi-experimental design, and (2) rare events or conditions.

Advantages of cross-sectional studies

Only one group is used and data are collected at only one time; therefore, such a study may be conducted relatively quickly without a lot of expense. The use of questionnaires is generally the cheapest method of data collection, but can result in a low response rate. This type of study is the best way to determine prevalence and may be used to identify associations that can then be studied with a cohort study to provide more evidence.

Advantages of case-control studies

Perfect observational study to use! Best way to study uncommon or rare conditions. Does not require very many subjects relative to cross-sectional and cohort studies. Can produce information that may be used for future, more elaborate studies, or provide evidence for grant applications.

Disadvantages of nonprobability sampling

Potential for selection bias (participants choose to participate due to interest). Likely to not be able to generalize findings to the general population - Biggest problem! Sampling error cannot be known.

Incidence versus Prevalence

Prevalence not a rate! Just percentage in population! Prevalence is at any given time. Incidence is over a certain period of time.

Purposive Sampling

Purposefully trying to get a certain kind of individual. - Snowball sampling (may be used to study individuals who are hard to identify or find). You basically identify one individual with the desired attribute and then use that individual to find others.

Systematic Review

Refers to a strict approach (i.e., clear set of rules) used for identify relevant studies; which includes the use of an accurate search strategy in order to identify all studies addressing a specific topic, the establishment of clear inclusion/exclusion criteria and a well-defined methodological analysis of the selected studies. The potential bias in identifying the studies is reduced, thus limited the possibility of the authors to select the studies arbitrarily considered the most "relevant" for supporting their own opinion or research hypotheses. Considered to provide the highest level of evidence.

Continuous assessment

Refers to the use of repeated observations of an action/behavior over time. Observations may take place several times a day or multiple times per week or months.

Potential sources of asymmetry in funnel plots

Selection biases - Publication, Location, Language, & Citation True Heterogeneity - Size of effect differs according to study size, Intensity of intervention, differences in underlying risk Data irregularities - Poor methodological design of small studies, Inadequate analysis, Fraud

Sampling error

The difference between the sample value (e.g., percentage of individuals diagnosed with PTSD) and the true value in the population

Disadvantages of cross-sectional studies

The use of questionnaires is generally the cheapest method of data collection, but can result in a low response rate and may result in biased data duet o potential differences in responders and nonresponders Data may be collected via interviews (in person or by phone); however, this method is more time consuming and expensive if several people must be hired to do interviews. Can't differentiate between cause and effect and therefore the researcher can't provide an explanation for the findings. Can only infer. Can't study rare outcomes or conditions. Even a large sample may miss detecting some one with the event.

Presenting the findings - Forest Plot

The usual way of displaying data from a meta-analysis is by a pictorial representation. This displays the findings from each individual study as a blob or square, with squares towards the left side indicating the new treatment to be better, whereas those on the right indicate the new treatment to be less effective. The size of the blob or square is proportional to the precision of the study.

A-B-A-B design (BEST DESIGN)

This design allows for two transitions (B to A and A to B) that can demonstrate the effectiveness of the treatment or intervention. This design strengthens the ability to draw a cause-and-effect conclusion between the intervention or treatment and the behavior. It is also the preferred design for single-case research. However, it could be considered unethical to return a participant (or case) to baseline in order to determine causality

Requirements for meta-analysis

Well-executed systematic review. However competent the meta-analysis, if the original review was partial, flawed or otherwise unsystematic, then the meta-analysis may provide a precise quantitative estimate that is simply wrong. The main requirement of systematic review is easier to state than to execute; a complete, unbiased collection of all the original studies of acceptable quality that examine the same therapeutic question.

Effect sizes for Chi-Square tests

When there is 1 DF for the chi-square test of independence, the effect size measure is phi. When there is more than 1 DF for the test of independence, the effect size measure you should use is Cramer's V.

Case study

a form of qualitative or mixed methods research. It involves an intense examination of an individual, a group, or an organization. Often referred to as ethnography, field study, and participant observation. They usually examine the relationship of, and interaction of, all variables in order to provide as complete an understanding of an event or situation as possible

Effect Size (ES)

a term used to measure the magnitude of a treatment or relationship effect. This is important because significance tests are a function of sample size. Effect size measures are NOT a function of sample size in single studies. They are the common currency of meta-analysis studies that summarize the findings from a specific area of research.

Hedges' g

is like the other measures based on a standardized difference, but its pooled standard deviation s* is computed slightly differently from Cohen's d. Hedge's ES measure will usually be lower or more conservative than Cohen's ES, but will approach Cohen's d as the sample size increases.

Cohen's d

is the effect size measure to use in the context of a t-test or one-way ANOVA on means. d is defined as the difference between two means divided by the pooled standard deviation for those means. Thus, in case where both samples are the same size, AS MEANS GET FARTHER APART, EFFECT SIZE IS BIGGER

Stability of performance

need data (i.e., measuring action/behavior) to be consistent/steady over time. Variability or fluctuation of measurements would make it difficult to draw any conclusions about the intervention

Descriptive case study approach

set to describe the natural phenomena which occur within the data in question, for instance, what different strategies are used by a reader and how the reader use them. An example of a descriptive case study is the journalistic description of the Watergate scandal by two reporters

The A-B design

simplest of the single-case design options. It is a simplified repeated measures design defined as A (baseline phase - no treatment or intervention) and B (treatment or intervention phase) To use this design, you need only to have repeated measurements of the problem or condition before your treatment (A) and then repeated measurements during the treatment period (B). The analysis is simply a comparison of the two sets of measurements.

Different phases

this simply refers to different conditions that the individual or case unit is exposed to during the study. A phase may be a baseline condition where there is no intervention or treatment condition. Another phase may refer to the time period where the individual case is receiving the treatment/intervention.