Cross-Sectional Design Vs. Longitudinal Designs
According to Berk (2014), longitudinal, cross-sectional, and sequential designs are forms of observational studies that research a particular variable and how it affects the participants over their lifespan. A longitudinal design measures a single individual or small group repeatedly over an extended period to provide information about changes. Regarding timeframe, longitudinal designs can relatively be short or long. On the contrary, a cross-sectional design can analyze people of diverse ages at a single moment in time. Since these studies have their pros and cons, we need a sequential study to rise above the conflicts of both cross-sectional and longitudinal design. This design will allow researchers to evaluate a cross-sectional or longitudinal
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sample on two or more occasions in a sequence to reveal how participants of each age cohort have transformed.
The individual difference, common patterns, and enhanced detailed information are major strengths longitudinal studies can display.
Alternatively, a drawback to a longitudinal study is that it is time-consuming, costly, and age-related variations may be inaccurate. Moreover, member dropout, practice, and cohort outcomes may lead to the original sample no longer are representative of the population in which researchers would like to use. (Papalia, Feldman, and Martorell, 2014). Meanwhile, a cross-sectional design is more favorable economically; furthermore, it can indicate similarities and differences among age groups and minimizes the possibility of participant dropout and practice outcomes (Berk, 2014). As mentioned previously, a cross-sectional and longitudinal research has their strength and weakness; nevertheless, to overcome those faults a sequential design is required. The asset of this type of analysis is that we can compare both cross-sectional and longitudinal. Furthermore, it can show us the cohort effects as well as the age-related changes more competently than the longitudinal or cross-sectional design alone. Be that as it may, it can still be costly, and it will require a prolonged amount of time, determination, and a sophisticated analysis of the data (Berk,
2014).
Cohort effects can be detrimental, given that one group may not affect other individuals developing at other times. The most compelling evidence is the research on social development that was conveyed during the World War II, in which the results would not apply to other decades such as the 1930s or 1960s due to the changes in history and culture (Berk, 2014). All things considered, I have seen that all designs are needed and used in specific ways based off of what needs investigation and what will work most efficiently for the research.
sample on two or more occasions in a sequence to reveal how participants of each age cohort have transformed.
The individual difference, common patterns, and enhanced detailed information are major strengths longitudinal studies can display.
Alternatively, a drawback to a longitudinal study is that it is time-consuming, costly, and age-related variations may be inaccurate. Moreover, member dropout, practice, and cohort outcomes may lead to the original sample no longer are representative of the population in which researchers would like to use. (Papalia, Feldman, and Martorell, 2014). Meanwhile, a cross-sectional design is more favorable economically; furthermore, it can indicate similarities and differences among age groups and minimizes the possibility of participant dropout and practice outcomes (Berk, 2014). As mentioned previously, a cross-sectional and longitudinal research has their strength and weakness; nevertheless, to overcome those faults a sequential design is required. The asset of this type of analysis is that we can compare both cross-sectional and longitudinal. Furthermore, it can show us the cohort effects as well as the age-related changes more competently than the longitudinal or cross-sectional design alone. Be that as it may, it can still be costly, and it will require a prolonged amount of time, determination, and a sophisticated analysis of the data (Berk,
2014).
Cohort effects can be detrimental, given that one group may not affect other individuals developing at other times. The most compelling evidence is the research on social development that was conveyed during the World War II, in which the results would not apply to other decades such as the 1930s or 1960s due to the changes in history and culture (Berk, 2014). All things considered, I have seen that all designs are needed and used in specific ways based off of what needs investigation and what will work most efficiently for the research.