Scientific Writing Guide

Scientific Writing Tips

• Use precise, simple language, focusing on clarity.
• Organize content logically, from sections to sentences.
• Emphasize truth and reader awareness: focus on clear communication.

Specific Writing Rules

• Ensure modifiers are clear and avoid ambiguity in sentence structure (e.g., "Journalists using cameras were observed" vs. "Cameras were used to observe the journalists").
• Colons introduce lists, while semicolons separate long items in a list or independent clauses.
• "That" is used for restrictive clauses (essential to meaning), and "Which" is used for non-restrictive clauses (extra information).

That & Which (and (non-) restrictive clauses)

• A non-restrictive clause provides additional information without changing the sentence's meaning. It is enclosed by commas.
• A restrictive clause is essential to the sentence's meaning. It is not enclosed by commas.

Main Sections of Empirical Reports

• Abstract: Concise summary (under 120-200 words) covering research focus, methods, key findings, and significance.
• Introduction: Introduces the topic, provides background information, and leads to research questions.
• Method: Details how the research was conducted, ensuring reproducibility.
• Results: Presents findings, starting with descriptive statistics and focusing on significant results.
• Discussion: Interprets findings, relating them to hypotheses and previous research, discusses limitations, suggests future directions, and concludes with key insights.
• Other Sections: Title page, references, author notes, footnotes, tables, and figures, all following specific guidelines.

Measurement

• Understand methods including direct observation, self-report/rating, and observer report/rating.

Types of Measurement Methods

• Direct Observation: Watching and recording behaviors directly.
  • Can be done in natural or artificial settings, live or through recordings, overtly (participants aware) or covertly (participants unaware), through ratings or counts.
  • Examples include observing children, mock juries, lab participants, or social media activity. Physiological and maximum-performance tests (like IQ) are also forms of direct observation.
  • Objective and verifiable, but costly and difficult to interpret.
• Reports and Ratings: Gathered through self-report or observer reports using questionnaires or interviews.
  • Reports can cover behavior tendencies or trait ratings.
  • Efficient but subjective; can be biased. Combining self-reports with multiple observers enhances accuracy.
• Biodata: Uses objective records (like school or court records) to gain insights.

Choosing a Measurement Method

• The best method depends on the nature of the research.

Reliability

• Refers to the extent to which similar measurements agree with each other.
• Measured by correlations among measurements.

Factors Influencing Reliability

• Number of Items or Judges: Reliability is higher with more items or judges.
• Correlation Among Items or Judges: Higher correlations indicate a stronger common element, increasing reliability.
• Common Element Concept: Aggregating items reduces the significance of unique elements in each item, improving overall reliability.

Reliability Formulas

• Spearman-Brown Formula: Used for internal consistency or inter-rater reliability.
  • Reliability = kr / 1 + (k-1)r
  • k = number of items or judges
  • r = average correlation between items or judges
  • Aggregating items or judges increases overall reliability.
• Coefficient Alpha (Cronbach's Alpha): More common in research, particularly for internal consistency reliability of scales or tests.
  • α = k / k-1 (1−​∑s^2item/​​−​s^2scale)
  • k = number of items
  • ​∑s^2item = sum of item variances
  • s^2scale = total scale variance
  • Represents the proportion of scale variance due to item covariance (excluding unique item variances).

Special Considerations

• Subscales require separate reliability measures like omega to account for variance common to all items and variance unique to individual subscales.
• Psychopathy assessments correlating with re-offending rates can offer valuable predictive insights.
• Even a modest correlation in criterion validity can be useful for predictions.

Additional Validity Types in Experimental Contexts

• Internal Validity: The independent variable is the only factor influencing the dependent variable.
• External Validity: Findings generalize to other settings, including real-world scenarios.

Multi-Trait Multi-Method Matrix (MTMM)

• A systematic approach to assess construct validity, specifically looking at convergent and discriminant validity while controlling for method variance.
• Ensures a measurement tool accurately captures the intended trait and is not merely reflecting the measurement method.

Confidence Intervals

• Smaller sample sizes may yield results significantly different from the population due to chance.
• Larger samples provide better estimates, as sampling error decreases with increasing sample size.
• For large populations, the absolute size of the sample matters more than the ratio of the sample size to the population size.
• As sample size increases, confidence intervals narrow for estimations of population proportions and means.
• Confidence intervals are wider when estimating differences between means across samples.
• Oversampling for small subpopulations can be used, but estimates for the whole population can then be adjusted by underweighting the oversampled group.

Explore essential tips and rules for effective scientific writing. This quiz covers the organization of content, clarity in language, and the proper use of clauses and punctuation in empirical reports. Test your understanding of writing principles to enhance your academic communication skills.